Single-particle motion under the influence of the perpendicular ponderomotive force

The motion of a single particle under the influence of the ponderomotive force directed perpendicular to the external magnetostatic field is analysed. By solving the exact equation of motion for a specific applied electromagnetic field, the resultant ponderomotive drift is compared with the prediction of a single-particle theory using the oscillation-centre approximation. The regime of validity of this theory is discussed. It is shown that, for certain values of the amplitude and frequency of the electromagnetic field, the particle motion is unstable and therefore the concept of a single-particle ponderomotive force is meaningles

Archetypes of agri-environmental potential: a multi-scale typology for spatial stratification and upscaling in Europe

Developing spatially-targeted policies for farmland in the European Union (EU) requires synthesized, spatially-explicit knowledge of agricultural systems and their environmental conditions. Such synthesis needs to be flexible and scalable in a way that allows the generalization of European landscapes and their agricultural potential into spatial units that are informative at any given resolution and extent. In recent years, typologies of agricultural lands have been substantially improved, however, agriculturally relevant aspects have yet to be included. We here provide a spatial classification approach for identifying archetypal patterns of agri-environmental potential in Europe based on machine-learning clustering of 17 variables on bioclimatic conditions, soil characteristics and topographical parameters. We improve existing typologies by (a) including more recent biophysical data (e.g. agriculturally-important soil parameters), (b) employing a fully data-driven approach that reduces subjectivity in identifying archetypal patterns, and (c) providing a scalable approach suitable both for the entire European continent as well as smaller geographical extents. We demonstrate the utility and scalability of our typology by comparing the archetypes with independent data on cropland cover and field size at the European scale and in three regional case studies in Germany, Czechia and Spain. The resulting archetypes can be used to support spatial stratification, upscaling and designation of more spatially-targeted agricultural policies, such as those in the context of the EU's Common Agricultural Policy post-2020

Archetypes of agri-environmental potential: a multi-scale typology for spatial stratification and upscaling in Europe

Developing spatially-targeted policies for farmland in the European Union (EU) requires synthesized, spatially-explicit knowledge of agricultural systems and their environmental conditions. Such synthesis needs to be flexible and scalable in a way that allows the generalization of European landscapes and their agricultural potential into spatial units that are informative at any given resolution and extent. In recent years, typologies of agricultural lands have been substantially improved, however, agriculturally relevant aspects have yet to be included. We here provide a spatial classification approach for identifying archetypal patterns of agri-environmental potential in Europe based on machine-learning clustering of 17 variables on bioclimatic conditions, soil characteristics and topographical parameters. We improve existing typologies by (a) including more recent biophysical data (e.g. agriculturally-important soil parameters), (b) employing a fully data-driven approach that reduces subjectivity in identifying archetypal patterns, and (c) providing a scalable approach suitable both for the entire European continent as well as smaller geographical extents. We demonstrate the utility and scalability of our typology by comparing the archetypes with independent data on cropland cover and field size at the European scale and in three regional case studies in Germany, Czechia and Spain. The resulting archetypes can be used to support spatial stratification, upscaling and designation of more spatially-targeted agricultural policies, such as those in the context of the EU's Common Agricultural Policy post-2020

Quick Ultra-VIolet Kilonova surveyor (QUVIK)

We present a near-UV space telescope on a ~70kg micro-satellite with a moderately fast repointing capability and a near real-time alert communication system that has been proposed in response to a call for an ambitious Czech national mission. The mission, which has recently been approved for Phase 0, A, and B1 study shall measure the brightness evolution of kilonovae, resulting from mergers of neutron stars in the near-UV band and thus it shall distinguish between different explosion scenarios. Between the observations of transient sources, the satellite shall perform observations of other targets of interest, a large part of which will be chosen in open competition.Comment: SPIE Astronomical Telescopes and Instrumentatio

How organic farmers view their own practice: results from the Czech Republic

This paper addresses the development of organic agriculture in the Czech Republic, which is seen as a success story among post-communist countries. The relatively short history of organic farming and specific contextual factors raises questions about the nature and meaning of Czech organic farming. The goal of this study was to find out how farmers view their own practice, interpret its symbolic value, and construct its content. This empirical study uses Q methodology aimed at the identification of the collectively-shared perspectives belonging engaged actors. Data were gathered through semi-standardized interviews with Czech farmers registered in official organic scheme. The analysis emphasized three components, which are considered as three distinct perspectives possessed by organic farmers; that is, (1) organic farming as a way of life, (2) as an occupation, and (3) as a production of food of an alternative quality compared to conventional food. Each viewpoint entails a different understanding of what organic farming means; each then—when considered together—comprises the meaning of organic agriculture in the Czech Republic. The presented classification of the farmers holding the viewpoints contributes to the ongoing theoretical discussion regarding the nature of the current organic sector, its development and potential conventionalization

Changes in habitat associations during range expansion: disentangling the effects of climate and residence time

The distributions of many species are not at equilibrium with their environment. This includes spreading non-native species and species undergoing range shifts in response to climate change. The habitat associations of these species may change during range expansion as less favourable climatic conditions at expanding range margins may constrain species to use only the most favourable habitats, violating the species distribution model assumption of stationarity. Alternatively, changes in habitat associations could result from density-dependent habitat selection; at range margins, population densities are initially low so species can exhibit density-independent selection of the most favourable habitats, while in the range core, where population densities are higher, species spread into less favourable habitat. We investigate if the habitat preferences of the non-native common waxbill Estrilda astrild changed as they spread in three directions (north, east and south-east) in the Iberian Peninsula. There are different degrees of climatic suitability and colonization speed across range expansion axes, allowing us to separate the effects of climate from residence time. In contrast to previous studies we find a stronger effect of residence time than climate in influencing the prevalence of common waxbills. As well as a strong additive effect of residence time, there were some changes in habitat associations, which were consistent with density-dependent habitat selection. The combination of broader habitat associations and higher prevalence in areas that have been colonised for longer means that species distribution models constructed early in the invasion process are likely to underestimate species’ potential distribution