Knowledge of the status of ecosystems is vital to help develop and implement conservation strategies. This is particularly relevant to the Arctic where the need for biodiversity conservation and monitoring has long been recognised, but where issues of local capacity and logistic barriers make surveys challenging. This paper demonstrates how long-term monitoring programmes outside the Arctic can contribute to developing composite trend indicators, using monitoring of annual abundance and population-level reproduction of species of migratory Arctic-breeding waterbirds on their temperate non-breeding areas. Using data from the UK and the Netherlands, countries with year-round waterbird monitoring schemes and supporting relevant shares of Arctic-breeding populations of waterbirds, we present example multi-species abundance and productivity indicators related to the migratory pathways used by different biogeographical populations of Arctic-breeding wildfowl and wader species in the East Atlantic Flyway. These composite trend indicators show that long-term increases in population size have slowed markedly in recent years and in several cases show declines over, at least, the last decade. These results constitute proof of concept. Some other non-Arctic countries located on the flyways of Arctic-breeding waterbirds also annually monitor abundance and breeding success, and we advocate that future development of “Arctic waterbird indicators” should be as inclusive of data as possible to derive the most robust outputs and help account for effects of current changes in non-breeding waterbird distributions. The incorporation of non-Arctic datasets into assessments of the status of Arctic biodiversity is recognised as highly desirable, because logistic constraints in monitoring within the Arctic region limit effective population-scale monitoring there, in effect enabling “monitoring at a distance”.

Predicting particle segregation has remained challenging due to the lack of a general model for the segregation velocity that is applicable across a range of granular flow geometries. Here, a segregation-velocity model for dense granular flows is developed by exploiting force balance and recent advances in particle-scale modelling of the segregation driving and drag forces over the entire particle concentration range, size ratios up to 3 and inertial numbers as large as 0.4. This model is shown to correctly predict particle segregation velocity in a diverse set of idealised and natural granular flow geometries simulated using the discrete element method. When incorporated in the well-established advection–diffusion–segregation formulation, the model has the potential to accurately capture segregation phenomena in many relevant industrial applications and geophysical settings.

Characterizing the structure and composition of clay minerals on the surface of Mars is important for reconstructing past aqueous processes and environments. Data from the CheMin X-ray diffraction (XRD) instrument on the Mars Science Laboratory Curiosity rover demonstrate a ubiquitous presence of collapsed smectite (basal spacing of 10 Å) in ~3.6-billion-year-old lacustrine mudstone in Gale crater, except for expanded smectite (basal spacing of 13.5 Å) at the base of the stratigraphic section in a location called Yellowknife Bay. Hypotheses to explain expanded smectite include partial chloritization by Mg(OH)2 or solvation-shell H2O molecules associated with interlayer Mg2+. The objective of this work is to test these hypotheses by measuring partially chloritized and Mg-saturated smectite using laboratory instruments that are analogous to those on Mars rovers and orbiters. This work presents Mars-analog XRD, evolved gas analysis (EGA), and visible/shortwave-infrared (VSWIR) data from three smectite standards that were Mg-saturated and partially and fully chloritized with Mg(OH)2. Laboratory data are compared with XRD and EGA data collected from Yellowknife Bay by the Curiosity rover to examine whether the expanded smectite can be explained by partial chloritization and what this implies about the diagenetic history of Gale crater. Spectral signatures of partial chloritization by hydroxy-Mg are investigated that may allow the identification of partially chloritized smectite in Martian VSWIR reflectance spectra collected from orbit or in situ by the SuperCam instrument suite on the Mars 2020 Perseverance rover. Laboratory XRD and EGA data of partially chloritized saponite are consistent with data collected from Curiosity. The presence of partially chloritized (with Mg(OH)2) saponite in Gale crater suggests brief interactions between diagenetic alkaline Mg2+-bearing fluids and some of the mudstone exposed at Yellowknife Bay, but not in other parts of the stratigraphic section. The location of Yellowknife Bay at the base of the stratigraphic section may explain the presence of alkaline Mg2+-bearing fluids here but not in other areas of Gale crater investigated by Curiosity. Early diagenetic fluids may have had a sufficiently long residence time in a closed system to equilibrate with basaltic minerals, creating an elevated pH, whereas diagenetic environments higher in the section may have been in an open system, therefore preventing fluid pH from becoming alkaline.

This review highlights the importance of dietary fibres (DF) intake and its interconnection with the gut microbiome and psychological well-being, while also exploring the effects of existing DF interventions on these aspects in adults. The gut microbiota is a complex and diverse ecosystem in which microbial species interact, influencing the human host. DF are heterogeneous, requiring different microbial species to degrade the complex DF structures. Emerging evidence suggests that microbial fermentation of DF produces short-chain fatty acids (SCFA), which may play a role in regulating psychological well-being by affecting neurotransmitter levels, including serotonin. The effectiveness of DF interventions depends on factors such as baseline gut microbiota composition, the dosage and the source of DF consumed. Although the gut microbiota of adults is relatively stable, studies have shown that the abundance of the species in the gut microbiota can change within 24 h of an intervention and may return to baseline following the termination of DF intervention. This review underscores the need for larger and well-powered dietary clinical trials incorporating longitudinal biological sample collections, advanced sequencing and omic techniques (including novel dietary biomarkers and microbial metabolites), validated subjective questionnaires and dietary records. Furthermore, mechanistic studies driven by clinical observations are crucial to understanding gut microbiota function and its underlying biological pathways, informing targeted dietary interventions.

The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.

Aerosol-cloud interactions contribute significant uncertainty to modern climate model predictions. Analysis of complex observed aerosol-cloud parameter relationships is a crucial piece of reducing this uncertainty. Here, we apply two machine learning methods to explore variability in in-situ observations from the NASA ACTIVATE mission. These observations consist of flights over the Western North Atlantic Ocean, providing a large repository of data including aerosol, meteorological, and microphysical conditions in and out of clouds. We investigate this dataset using principal component analysis (PCA), a linear dimensionality reduction technique, and an autoencoder, a deep learning non-linear dimensionality reduction technique. We find that we can reduce the dimensionality of the parameter space by more than a factor of 2 and verify that the deep learning method outperforms a PCA baseline by two orders of magnitude. Analysis in the low dimensional space of both these techniques reveals two consistent physically interpretable regimes—a low pollution regime and an in-cloud regime. Through this work, we show that unsupervised machine learning techniques can learn useful information from in-situ atmospheric observations and provide interpretable results of low-dimensional variability.

Basal channels are incised troughs formed by elevated melt beneath ice shelves. Channels often coincide with shear margins, suggesting feedbacks between channel formation and shear. However, the effect of channel position and shape on ice-shelf flow has not been systematically explored. We use a model to show that, as expected, channels concentrate deformation and increase ice-shelf flow speeds, in some cases by over 100% at the ice-shelf center and over 80% at the grounding line. The resulting increase in shear can cause stresses around the channels to exceed the threshold for failure, suggesting that rifting, calving and retreat might result. However, channels have different effects depending on their width, depth and position on an ice shelf. Channels in areas where ice shelves are spreading freely have little effect on ice flow, and even channels in confined regions of the shelf do not necessarily alter flow significantly. Nevertheless, if located in areas of vulnerability, particularly in the shear margins near the grounding line, melt channels may alter flow in a way that could lead to catastrophic ice-shelf breakup by mechanically separating shelves from their embayments.

Lift and drag forces on moving intruders in flowing granular materials are of fundamental interest but have not yet been fully characterized. Drag on an intruder in granular shear flow has been studied almost exclusively for the intruder moving across flow streamlines, and the few studies of the lift explore a relatively limited range of parameters. Here, we use discrete element method simulations to measure the lift force, $F_{{L}}$, and the drag force on a spherical intruder in a uniformly sheared bed of smaller spheres for a range of streamwise intruder slip velocities, $u_{{s}}$. The streamwise drag matches the previously characterized Stokes-like cross-flow drag. However, $F_{{L}}$ in granular shear flow acts in the opposite direction to the Saffman lift in a sheared fluid at low $u_{{s}}$, reaches a maximum value and then decreases with increasing $u_{{s}}$, eventually reversing direction. This non-monotonic response holds over a range of flow conditions, and the $F_{{L}}$ versus $u_{{s}}$ data collapse when both quantities are scaled using the particle size, shear rate and overburden pressure. Analogous fluid simulations demonstrate that the flow around the intruder particle is similar in the granular and fluid cases. However, the shear stress on the granular intruder is notably less than that in a fluid shear flow. This difference, combined with a void behind the intruder in granular flow in which the stresses are zero, significantly changes the lift-force-inducing stresses acting on the intruder between the granular and fluid cases.

The fossil record of dinosaurs in Scotland mostly comprises isolated highly fragmentary bones from the Great Estuarine Group in the Inner Hebrides (Bajocian–Bathonian). Here we report the first definite dinosaur body fossil ever found in Scotland (historically), having been discovered in 1973, but not collected until 45 years later. It is the first and most complete partial dinosaur skeleton currently known from Scotland. NMS G.2023.19.1 was recovered from a challenging foreshore location in the Isle of Skye, and transported to harbour in a semi-rigid inflatable boat towed by a motor boat. After manual preparation, micro-CT scanning was carried out, but this did not aid in identification. Among many unidentifiable elements, a neural arch, two ribs and part of the ilium are described herein, and their features indicate that this was a cerapodan or ornithopod dinosaur. Histological thin sections of one of the ribs support this identification, indicating an individual at least eight years of age, growing slowly at the time of death. If ornithopodan, as our data suggest, it could represent the world's oldest body fossil of this clade.

To protect inframarginal rents, rivals react to competition shocks by increasing product differentiation or lowering costs by standardizing products and production processes. We test these two mutually exclusive reactions by exploiting changes in rivals’ idiosyncratic stock return comovement following significant tariff cuts. While increased product differentiation implies a reduction in return comovement, greater standardization implies the opposite (a comovement increase). Difference-in-differences (DID) tests indicate that tariff cuts cause a significant increase in return comovement—in particular among within-industry “followers.” Treatment effects on cash flows, product counts, similarity scores, and business segment counts further support cost-cutting strategies.

Observation of thin sections of the WAIS (West Antarctic Ice Sheet) Divide ice core in cross-polarized light reveals a wealth of microstructures and textural characteristics indicative of strain and recovery in an anisotropic crystalline substance undergoing high-temperature plastic deformation. The appearance of abundant subgrain domains—relatively strain-free regions inside crystals (grains) surrounded by walls of dislocations across which small structural orientation changes occur—is particularly noticeable in the depth range associated with the brittle ice (∼650–1300 m). Here we describe a subgrain texture, not previously reported in ice, that resembles chessboard-pattern subgrains in β-quartz. This chessboard texture at WAIS Divide is strongly associated with the presence of bubbles. We hypothesize that chessboard-subgrain development may affect grain-size evolution, the fracture of ice cores recovered from the brittle ice zone and perhaps grain-boundary sliding as well.

Methods developed by Bernbach [1966] and Millward [1969] permit increased generality in analyses of identifiability. Matrix equations are presented that solve part of the identifiability problem for a class of Markov models. Results of several earlier analyses are shown to involve special cases of the equations developed here. And it is shown that a general four-state chain has the same parameter space as an all-or-none model if and only if its representation with an observable absorbing state is lumpable into a Markov chain with three states.