Drivers of European bat population change: a review reveals evidence gaps

Bat populations are thought to have suffered significant declines in the past century throughout Europe. Fortunately, there are some signs of recovery; for instance, of the 11 species monitored in the UK, population trends of five are increasing. The drivers of past losses and recent trends are unclear; identifying them will enable targeted conservation strategies to support further recovery. We review the evidence linking proposed drivers to impacts on bat populations in Europe, using the results of a previous cross‐taxa semi‐quantitative assessment as a framework. Broadly, the drivers reviewed relate to land‐use practices, climate change, pollution, development and infrastructure, and human disturbance. We highlight where evidence gaps or conflicts present barriers to successful conservation and review emerging opportunities to address these gaps. We find that the relative importance or impacts of the potential drivers of bat population change are not well understood or quantified, with conflicting evidence in many cases. To close key gaps in the evidence for responses of bat populations to environmental change, future studies should focus on the impacts of climate change, urbanisation, offshore wind turbines, and water pollution, as well as on mitigation measures and the synergistic effects of putative drivers. To increase available evidence of drivers of bat population change, we propose utilising advances in monitoring tools and statistical methods, together with robust quantitative assessment of conservation interventions to mitigate threats and enable the effective conservation of these protected species

On the accuracy of retrieved wind information from Doppler lidar observations

A single pulsed Doppler lidar was successfully deployed to measure air flow and turbulence over the Malvern hills, Worcester, UK. The DERA Malvern lidar used was a CO2 µm pulsed Doppler lidar. The lidar pulse repetition rate was 120 Hz and had a pulse duration of 0.6 µs The system was set up to have 41 range gates with range resolution of 112 m. This gave a theoretical maximum range of approximately 4.6 km. The lidar site was 2 km east of the Malvern hill ridge which runs in a north-south direction and is approximately 6 km long. The maximum height of the ridge is 430 m. Two elevation scans (Range-Height Indicators) were carried out parallel and perpendicular to the mean surface flow. Since the surface wind was primarily westerly the scans were carried out perpendicular and parallel to the ridge of the Malvern hills. The data were analysed and horizontal winds, vertical winds and turbulent fluxes were calculated for profiles throughout the boundary layer. As an aid to evaluating the errors associated with the derivation of velocity and turbulence profiles, data from a simple idealized profile was also analysed using the same method. The error analysis shows that wind velocity profiles can be derived to an accuracy of 0.24 m s-1 in the horizontal and 0.3 m s-1 in the vertical up to a height of 2500 m. The potential for lidars to make turbulence measurements, over a wide area, through the whole depth of the planetary boundary layer and over durations from seconds to hours is discussed

Smoothing in linear multicompartment biological processes subject to stochastic input

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before the eventual accumulation and release of replicated virions. While such systems may have some control over the internal dynamics that make up this progression, a challenge for many is to regulate behaviour under what are often highly variable external environments acting as system inputs. In this work, we study a simple analogue of this problem through a linear multicompartment model subject to a stochastic input in the form of a mean-reverting Ornstein-Uhlenbeck process, a type of Gaussian process. By expressing the system as a multidimensional Gaussian process, we derive several closed-form analytical results relating to the covariances and autocorrelations of the system, quantifying the smoothing effect discrete compartments afford multicompartment systems. Semi-analytical results demonstrate that feedback and feedforward loops can enhance system robustness, and simulation results probe the intractable problem of the first passage time distribution, which has specific relevance to eventual cell lysis in the viral replication cycle. Finally, we demonstrate that the smoothing seen in the process is a consequence of the discreteness of the system, and does not manifest in an equivalent continuum limit description. While we make progress through analysis of a simple linear problem, many of our insights are applicable more generally, and our work enables future analysis into multicompartment processes subject to stochastic inputs

About Those New Oats - Burnett and Newton

These two new oat varieties will be available for planting in 1958. You can see them growing this year at Iowa State College or in the fields of certified seed producers. Here are the details on what you can expect

Smoothing in linear multicompartment biological processes subject to stochastic input

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before the eventual accumulation and release of replicated virions. While such systems may have some control over the internal dynamics that make up this progression, a challenge for many is to regulate behaviour under what are often highly variable external environments acting as system inputs. In this work, we study a simple analogue of this problem through a linear multicompartment model subject to a stochastic input in the form of a mean-reverting Ornstein-Uhlenbeck process, a type of Gaussian process. By expressing the system as a multidimensional Gaussian process, we derive several closed-form analytical results relating to the covariances and autocorrelations of the system, quantifying the smoothing effect discrete compartments afford multicompartment systems. Semi-analytical results demonstrate that feedback and feedforward loops can enhance system robustness, and simulation results probe the intractable problem of the first passage time distribution, which has specific relevance to eventual cell lysis in the viral replication cycle. Finally, we demonstrate that the smoothing seen in the process is a consequence of the discreteness of the system, and does not manifest in system with continuous transport. While we make progress through analysis of a simple linear problem, many of our insights are applicable more generally, and our work enables future analysis into multicompartment processes subject to stochastic inputs.Comment: 6 figures, includes supplementary documen

Particle Acceleration and Their Escape into the Heliosphere in Solar Flares with Open Magnetic Field

© 2023, The Author(s). Published by the American Astronomical Society. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Energetic particle populations in the solar corona and in the heliosphere appear to have different characteristics even when produced in the same solar flare. It is not clear what causes this difference: properties of the acceleration region, the large-scale magnetic field configuration in the flare, or particle transport effects, such as scattering. In this study, we use a combination of magnetohydrodynamic and test-particle approaches to investigate magnetic reconnection, particle acceleration, and transport in two solar flares: an M-class flare on 2013 June 19, and an X-class flare on 2011 September 6. We show that in both events, the same regions are responsible for the acceleration of particles remaining in the coronal and being ejected toward the heliosphere. However, the magnetic field structure around the acceleration region acts as a filter, resulting in different characteristics (such as energy spectra) acquired by these two populations. We argue that this effect is an intrinsic property of particle acceleration in the current layers created by the interchange reconnection, and therefore, may be ubiquitous, particularly, in noneruptive solar flares with substantial particle emission into the heliosphere.Peer reviewe

Development of a chromium-thoria alloy

Low temperature ductility and high temperature strength of pure chromium and chromium-thoria alloy prepared from vapor deposited powder

Simulations of dynamo action in fully convective stars

We present three-dimensional nonlinear magnetohydrodynamic simulations of the interiors of fully convective M-dwarfs. Our models consider 0.3 solar-mass stars using the Anelastic Spherical Harmonic code, with the spherical computational domain extending from 0.08-0.96 times the overall stellar radius. Like previous authors, we find that fully convective stars can generate kG-strength magnetic fields (in rough equipartition with the convective flows) without the aid of a tachocline of shear. Although our model stars are everywhere unstably stratified, the amplitudes and typical pattern sizes of the convective flows vary strongly with radius, with the outer regions of the stars hosting vigorous convection and field amplification while the deep interiors are more quiescent. Modest differential rotation is established in hydrodynamic calculations, but -- unlike in some prior work --strongly quenched in MHD simulations because of the Maxwell stresses exerted by the dynamo-generated magnetic fields. Despite the lack of strong differential rotation, the magnetic fields realized in the simulations possess significant mean (axisymmetric) components, which we attribute partly to the strong influence of rotation upon the slowly overturning flows.Comment: Accepted to the ApJ. 20 pages (emulateapj), 4 color figures compressed to low-resolution; higher-resolution equivalents are available at http://lcd-www.colorado.edu/~brownim/browning_2007_mstars.pd

Optimal algorithms for haplotype assembly from whole-genome sequence data

Motivation: Haplotype inference is an important step for many types of analyses of genetic variation in the human genome. Traditional approaches for obtaining haplotypes involve collecting genotype information from a population of individuals and then applying a haplotype inference algorithm. The development of high-throughput sequencing technologies allows for an alternative strategy to obtain haplotypes by combining sequence fragments. The problem of ‘haplotype assembly’ is the problem of assembling the two haplotypes for a chromosome given the collection of such fragments, or reads, and their locations in the haplotypes, which are pre-determined by mapping the reads to a reference genome. Errors in reads significantly increase the difficulty of the problem and it has been shown that the problem is NP-hard even for reads of length 2. Existing greedy and stochastic algorithms are not guaranteed to find the optimal solutions for the haplotype assembly problem