Fast and accurate frequency-dependent radiation transport for hydrodynamics simulations in massive star formation

Context: Radiative feedback plays a crucial role in the formation of massive stars. The implementation of a fast and accurate description of the proceeding thermodynamics in pre-stellar cores and evolving accretion disks is therefore a main effort in current hydrodynamics simulations. Aims: We introduce our newly implemented three-dimensional frequency dependent radiation transport algorithm for hydrodynamics simulations of spatial configurations with a dominant central source. Methods: The module combines the advantage of the speed of an approximate Flux Limited Diffusion (FLD) solver with the high accuracy of a frequency dependent first order ray-tracing routine. Results: We prove the viability of the scheme in a standard radiation benchmark test compared to a full frequency dependent Monte-Carlo based radiative transfer code. The setup includes a central star, a circumstellar flared disk, as well as an envelope. The test is performed for different optical depths. Considering the frequency dependence of the stellar irradiation, the temperature distributions can be described precisely in the optically thin, thick, and irradiated transition regions. Resulting radiative forces onto dust grains are reproduced with high accuracy. The achievable parallel speedup of the method imposes no restriction on further radiative (magneto-) hydrodynamics simulations. Conclusions: The proposed approximate radiation transport method enables frequency dependent radiation hydrodynamics studies of the evolution of pre-stellar cores and circumstellar accretion disks around an evolving massive star in a highly efficient and accurate manner.Comment: 16 pages, 11 figure

A comparison of conventional and 137 Cs-based estimates of soil erosion rates on arable and grassland across lowland England and Wales

Soils deliver a range of ecosystem services and underpin conventional global food production which must increase to feed the projected growth in human population. Although soil erosion by water and subsequent sediment delivery to rivers are natural processes, anthropogenic pressures, including modern farming practices and management, have accelerated soil erosion rates on both arable and grassland. A range of approaches can be used to assess and document soil erosion rates and, in the case of the UK, these mainly comprise the 137Cs-based approach, conventional surveys using volumetric measurements, integration of information on suspended sediment flux, fine sediment source apportionment and landscape sediment retention and traditional bounded hydrological monitoring at edge-of-field using experimental platforms. We compare the erosion rates for arable and grassland in lowland England assessed by these different techniques. Rates assessed by volumetric measurements are similar to those generated by integrating information on suspended sediment flux, sources and landscape retention, but are much less than those estimated by the 137Cs-based approach; of the order of one magnitude less for arable land. The 137Cs approach assumes an initial distribution of 137Cs uniformly spread across the landscape and relates the sampled distribution to erosion, but other (transport) processes are also involved and their representation in the calibration procedures remains problematic. We suggest that the 137Cs technique needs to be validated more rigorously and conversion models re-calibrated. As things stand, rates of erosion based on the distribution of 137Cs may well overstate the severity of the problem in lowland Britain and, therefore, are not a reliable indicator of water erosion rates

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

The impact of catchment source group classification on the accuracy of sediment fingerprinting outputs

The objective classification of sediment source groups is at present an under-investigated aspect of source tracing studies, which has the potential to statistically improve discrimination between sediment sources and reduce uncertainty. This paper investigates this potential using three different source group classification schemes. The first classification scheme was simple surface and subsurface groupings (Scheme 1). The tracer signatures were then used in a two-step cluster analysis to identify the sediment source groupings naturally defined by the tracer signatures (Scheme 2). The cluster source groups were then modified by splitting each one into a surface and subsurface component to suit catchment management goals (Scheme 3). The schemes were tested using artificial mixtures of sediment source samples. Controlled corruptions were made to some of the mixtures to mimic the potential causes of tracer non-conservatism present when using tracers in natural fluvial environments. It was determined how accurately the known proportions of sediment sources in the mixtures were identified after unmixing modelling using the three classification schemes. The cluster analysis derived source groups (2) significantly increased tracer variability ratios (inter-/ intra-source group variability) (up to 2122%, median 194%) compared to the surface and subsurface groupings (1). As a result, the composition of the artificial mixtures was identified an average of 9.8% more accurately on the 0e100% contribution scale. It was found that the cluster groups could be reclassified into a surface and subsurface component (3) with no significant increase in composite uncertainty(a 0.1% increase over Scheme 2). The far smaller effects of simulated tracer non-conservatism for the cluster analysis based schemes (2 and 3) was primarily attributed to the increased inter-group variability producing a far larger sediment source signal that the non-conservatism noise (1). Modified cluster analysis based classification methods have the potential to reduce composite uncertainty significantly in future source tracing studies

Hormonally mediated effects of artificial light at night on behavior and fitness: linking endocrine mechanisms with function.

Alternation between day and night is a predictable environmental fluctuation that organisms use to time their activities. Since the invention of artificial lighting, this predictability has been disrupted and continues to change in a unidirectional fashion with increasing urbanization. As hormones mediate individual responses to changing environments, endocrine systems might be one of the first systems affected, as well as being the first line of defense to ameliorate any negative health impacts. In this Review, we first highlight how light can influence endocrine function in vertebrates. We then focus on four endocrine axes that might be affected by artificial light at night (ALAN): pineal, reproductive, adrenal and thyroid. Throughout, we highlight key findings, rather than performing an exhaustive review, in order to emphasize knowledge gaps that are hindering progress on proposing impactful and concrete plans to ameliorate the negative effects of ALAN. We discuss these findings with respect to impacts on human and animal health, with a focus on the consequences of anthropogenic modification of the night-time environment for non-human organisms. Lastly, we stress the need for the integration of field and lab experiments as well as the need for long-term integrative eco-physiological studies in the rapidly expanding field of light pollution

Switching Aurora-A kinase on and off at an allosteric site

Protein kinases are central players in the regulation of cell cycle and signalling pathways. Their catalytic activities are strictly regulated through post-translational modifications and protein–protein interactions that control switching between inactive and active states. These states have been studied extensively using protein crystallography, although the dynamic nature of protein kinases makes it difficult to capture all relevant states. Here, we describe two recent structures of Aurora-A kinase that trap its active and inactive states. In both cases, Aurora-A is trapped through interaction with a synthetic protein, either a single-domain antibody that inhibits the kinase or a hydrocarbon-stapled peptide that activates the kinase. These structures show how the distinct synthetic proteins target the same allosteric pocket with opposing effects on activity. These studies pave the way for the development of tools to probe these allosteric mechanisms in cells