Successful evacuation of a peculiar 'colony' of the wood ant Formica polyctena Forst., for years trapped within an old bunker previously used for storing nuclear weapons (see Czechowski et al. 2016), is reported. Using an experimentally installed boardwalk, the imprisoned ants managed to get through the ventilation pipe to their maternal nest on the top of the bunker. In our previous report, we left open the question of how the 'colony' could survive seemingly without food. Here we show that the 'colony' in the bunker survived and grew thanks to an influx of workers from the source nest above the bunker and mass consumption of corpses of the imprisoned nestmates.

Sensitivity of two-proton emitting decay to nuclear pairing correlation is discussed within a time-dependent three-body model. We focus on the Be-6 nucleus assuming alpha + p + p configuration, and its decay process is described as a time evolution of the three-body resonance state. For a proton-proton subsystem, a schematic density-dependent contact (SDDC) pairing model is employed. From the time-dependent calculation, we observed the exponential decay rule of a two-proton emission. It is shown that the density dependence does not play a major role in determining the decay width, which can be controlled only by the asymptotic strength of the pairing interaction. This asymptotic pairing sensitivity can be understood in terms of the dynamics of the wave function driven by the three-body Hamiltonian, by monitoring the time-dependent density distribution. With this simple SDDC pairing model, there remains an impossible trinity problem: it cannot simultaneously reproduce the empirical Q value, decay width, and the nucleon-nucleon scattering length. This problem suggests that a further sophistication of the theoretical pairing model is necessary, utilizing the two-proton radioactivity data as the reference quantities.

We perform the first numerical simulations of necklaces in a non-Abelian gauge theory. Necklaces are composite classical solutions which can be interpreted as monopoles trapped on strings, rather generic structures in a Grand Unified Theory. We generate necklaces from random initial conditions, modeling a phase transition in the early Universe, and study the evolution. For all cases, we find that the necklace system shows scaling behavior similar to that of a network of ordinary cosmic strings. Furthermore, our simulations indicate that comoving distance between the monopoles or semipoles along the string asymptotes to a constant value at late times. This means that, while the monopole-to-string energy density ratio decreases as the inverse of the scale factor, a horizon-size length of string has a large number of monopoles, significantly affecting the dynamics of string loops. We argue that gravitational wave bounds from millisecond pulsar timing on the string tension in the Nambu-Goto scenario are greatly relaxed.

Examining changes in abundance and demographic rates at species distribution margins may provide the first signs of broader species responses to environmental change. Still, the joint impact of space and time have remained relatively unstudied in most marginal regions. In order to examine the influence of climate variability on mussel distribution patterns, we monitored three sublittoral and marginal blue mussel (Mytilus trossulus) populations, spaced along a salinity gradient. Densities and biomasses peaked toward the saltier parts of the study area and showed relatively larger variations toward the low saline edge. Temporally, the areas showed a consistent increase in abundance after a synchronized large-scale recruitment event, which was followed by a decline in population size, occurring much faster toward the very range edge. Salinity, temperature, winter severity, and wave exposure explained most of the spatiotemporal variation in mussel abundances and adults showed positive effects on recruit abundance. We show empirically that the dynamics of edge populations are not driven by large changes in climate variables but that small spatial and temporal changes in key environmental variables have large and non-linear population level effects. Our results also show that fluctuating recruitment is a key factor for population stability affecting the storage potential of marginal populations, which dramatically decrease toward the edge. Our study provides a window into future population patterns and processes that drive marginal mussel populations in an altered sea characterized by rising temperature and declining salinity.

Aim To better understand and more realistically predict future species distribution ranges, it is critical to account for local adaptation and phenotypic plasticity in populations' responses to climate. This is challenging because local adaptation and phenotypic plasticity are trait-dependent and traits covary along climatic gradients, with differential consequences for fitness. Our aim is to quantify local adaptation and phenotypic plasticity of vertical and radial growth, leaf flushing and survival across the range of Fagus sylvatica and to estimate the contribution of each trait to explaining the species' occurrence. Location Europe. Time period 1995-2014; 2070. Major taxa studied Fagus sylvatica L. Methods We used vertical and radial growth, flushing phenology and mortality of F. sylvatica L. recorded in the BeechCOSTe52 database (>150,000 trees). Firstly, we performed linear mixed-effect models that related trait variation and covariation to local adaptation (related to the planted populations' climatic origin) and phenotypic plasticity (accounting for the climate of the plantation), and we made spatial predictions under current and representative concentration pathway (RCP 8.5) climates. Secondly, we combined spatial trait predictions in a linear model to explain the occurrence of the species. Results The contribution of plasticity to intraspecific trait variation is always higher than that of local adaptation, suggesting that the species is less sensitive to climate change than expected; different traits constrain beech's distribution in different parts of its range: the northernmost edge is mainly delimited by flushing phenology (mostly driven by photoperiod and temperature), the southern edge by mortality (mainly driven by intolerance to drought), and the eastern edge is characterized by decreasing radial growth (mainly shaped by precipitation-related variables in our model); considering trait covariation improved single-trait predictions. Main conclusions Population responses to climate across large geographical gradients are dependent on trait x environment interactions, indicating that each trait responds differently depending on the local environment.

Context. The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals. Aims. Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF). Methods. We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory. Results. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3-5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5-10 s, and the inference time is sufficiently small (