Ammonoid cephalopods are excellent model systems for evolutionary biomechanics due to their volatile evolutionary dynamics and remarkable fossil record. During the Mesozoic marine revolution, natural selection increasingly favored ammonoid shells with specific ranges of ornamentation patterns (projections that influence surface roughness). While this evolutionary pattern has been attributed to enemy-driven evolution (i.e., escalation), many morphologies lack clear defensive roles. Using a combination of 3D modeling, physical experiments, and computer simulations, we investigate these patterns from a hydromechanical perspective. We model theoretical morphologies along a continuum of increasing ornamentation coarseness. Neutrally buoyant, 3D-printed models, weighted to match the mass distribution of their virtual counterparts, demonstrate that coarser patterns progressively attenuate rocking motions. Flow visualization experiments reveal these coarser patterns produce higher energy dissipation rates in the disturbed fluid. Computational fluid dynamics simulations were performed to characterize the hydrodynamic costs of ornamentation patterns over the majority of biologically relevant swimming speeds and shell sizes for planispiral ammonoids. Only the coarsest categories incur substantial increases in hydrodynamic drag. However, ornamentation patterns with intermediate coarseness effectively avoid this physical trade-off, experiencing dynamic stabilization without considerably reducing swimming efficiency. These trade-off-defying morphologies were progressively favored during the Mesozoic, becoming more abundant than others by the end of this era. Ultimately, these experiments highlight important hydromechanical selective pressures involved in ammonoid evolutionary trends and some fundamental constraints on aquatic locomotion more broadly.

Visible satellite imagery (VIS) is essential for monitoring weather patterns and tracking ground surface changes associated with climate change. However, its availability is limited during nighttime. To address this limitation, we present a discrete variational autoencoder (VQVAE) method for translating infrared satellite imagery to VIS. This method departs from previous efforts that utilize a U-Net architecture. By removing the connections between corresponding layers of the encoder and decoder, the model learns a discrete and rich codebook of latent priors for the translation task. We train and test our model on mesoscale data from the Geostationary Operational Environmental Satellite (GOES) West Advanced Baseline Imager (ABI) sensor, spanning 4 years (2019 to 2022) using the Conditional Generative Adversarial Nets (CGAN) framework. This work demonstrates the practical use of a VQVAE for meteorological satellite image translation. Our approach provides a modular framework for data compression and reconstruction, with a latent representation space specifically designed for handling meteorological satellite imagery.

The Great Ordovician Biodiversification Event (GOBE) records a global increase in marine biodiversity that reached maximum diversification rates during the Middle Ordovician. The degree to which the causes of the GOBE are regional or global is a question that must be addressed through analysis of regional data. In this study, stratigraphically constrained field-based data from the Middle Ordovician Simpson Group of Oklahoma were collected to identify temporal trends in body volume and determine whether body volume trends are more closely associated regional or global environmental and diversity changes. Anteroposterior–transverse (AT) volume estimations were produced for rhynchonelliform brachiopods at a bedding-plane level of resolution. Time-series analysis was used to establish temporal trends in brachiopod volume. Volume data were then analyzed alongside paired δ18O, Δ13C, 87Sr/86Sr, taxonomic diversity, and lithologic data using a boosted regression model to identify their relative influence on shell volume through time. Results of these analyses indicate that (1) a rapid pulse of brachiopod volume increase occurred coincident with the main diversification pulse in Simpson Group strata and (2) volume increase was not coupled with an increase in brachiopod volume variance. Volume increase was primarily associated with global-scale factors such as age, δ18O (temperature), 87Sr/86Sr (tectonics), and taxonomic diversity trends; whereas local-scale factors of Δ13C (carbon cycle) and lithologic trends were more weakly associated with local volume trends. Notably, all factors had a nonzero influence over brachiopod volume, indicating that local diversification was influenced by multifaceted interactions among abiotic and biotic controls. These results support the argument that Ordovician diversification included a substantial biotic shift during the Middle Ordovician and support the hypothesis that global factors were dominant, influencing diversification patterns during the main phase of the GOBE.

This study introduces a custom implementation of the Ensemble Kalman Filter (EnKF) for calibrating a three-dimensional glacier evolution model. The EnKF can assimilate observations as they become available and provides uncertainty measures for the initial state after calibration. We calibrate an elevation-dependent surface mass balance (SMB) model using elevation change observations and test the EnKF’s performance in a Twin Experiment by varying internal and external hyperparameters. The best-performing configuration is applied to the Rhône Glacier in a Real-World Experiment. Using satellite-based elevation change fields for calibration, the EnKF estimates an average equilibrium line altitude of $2920 \pm 37$ m for the period 2000–19. A comparison of the results with glaciological measurements demonstrates the capabilities of the EnKF to simultaneously calibrate multiple SMB parameters. With this proof of concept, we expect that our methodology is readily extendable to other map or point observations and their combination, as well as to other calibration parameters.

Coastal nature-based solution (NBS) projects have been on the rise over the past few years. In France, the expression is being increasingly used at a local level, and new projects are developing on the coast. However, they face various limitations, involving both technical challenges and social acceptability issues. Based on data from the perception survey conducted by the DIGUES research programme in the Authie Bay in 2021 and a numerical model used to assess the efficiency of flood protection measures developed as part of a flood action and prevention programme, this study aimed to highlight the gap between perceptions and misconceptions surrounding NBS-like scenarios and more objective modelling data. It offers a cross-comparison of these two datasets. For this purpose, the scenarios used to assess public perception in the DIGUES survey were translated in the numerical model to study the difference between perceived protection and actual protection in the Authie Bay, the opportunity for dyke relocation in an NBS scenario, and the effectiveness of the NBSs according to their scale. Overall, these results demonstrated a real benefit for implementing dyke relocation through breaches, compared to other scenarios for the Authie Bay.

Glacial lakes in the Himalayas have expanded significantly in recent decades, increasing the potential risk of outburst floods. However, limited field surveys and systematic assessments leave downstream communities vulnerable. Accurate volume estimation of glacial lakes is essential for modelling flood dynamics, yet in-situ bathymetric data remain scarce. In this study, we surveyed four glacial lakes—Kya Tso Lake, Panchi Nala Lake, Gepang Gath Lake and Samudra Tapu Lake—in the Chandrabhaga basin, western Himalayas. Depth measurements were conducted using a portable inflatable kayak in August 2022 and an echo sounder mounted on an uncrewed surface vehicle in August 2024. Bathymetric modelling revealed maximum depths of 16 m, 10 m, 46 m, and 59 m, with corresponding storage capacities of 0.89, 0.44, 24.12, and 24.69 × 10⁶ m3, respectively. Volume estimates derived from empirical equations showed substantial discrepancies of ± 36–1736% compared to in-situ measurements. Despite several operational challenges, this study provides valuable in-situ bathymetric data for future modelling and hazard assessment of rapidly expanding glacial lakes in the region. The findings emphasise the need for robust field-based bathymetric datasets to refine empirical volume estimation models for Himalayan glacial lakes.

Greenland’s peripheral glaciers and ice caps contribute disproportionately to sea-level rise relative to their small area. Winter snow accumulation directly influences glacier mass balance and downstream hydrology, but spatially extensive observations of this important mass balance component remain sparse. In this study, we present a unique multi-year (2008–2024) dataset of winter snow accumulation over A.P. Olsen Ice Cap, Northeast Greenland, from ground-penetrating radar surveys covering an average of 47 km per survey year. Our results reveal strong spatial heterogeneity that is likely influenced by wind redistribution and local topography, especially in the ablation zone. We compare our findings with automatic weather station data from three sites and outputs from the Copernicus Arctic Regional Reanalysis (CARRA). Governed by the high spatial variability, the automatic weather station point-based observations significantly underestimate regional accumulation by 40–45%. Despite the high spatial variability, the CARRA accumulated precipitation variable provides a reasonable overall mean winter snow accumulation (RMSE of 0.07 m w.e.); however, it fails to reproduce the complex non-linear relationship between snow depth and elevation observed in the radar data. Our findings emphasize the need for high-resolution, spatially extensive measurements to better understand snow accumulation on ice caps and glaciers and improve reanalysis assessments.

Wastewater treatment is critically important and ceramic-membrane engineering is one of the most effective technologies for water filtration and purification. However, the materials used in the preparation of ceramic membranes are usually expensive, e.g. ZrO and Al2O3 membranes, reverse osmosis materials such as carbon-based thin-film nanocomposite TFNC ‘carbon nanotube, graphene-oxide’. Delicate, thin membranes employed for small-scale filtration usually require optimal supports for effective operation. The purpose of the present research, therefore, was to find a less expensive material for membrane supports while, at the same time, enhancing performance. Membrane supports were thus prepared from local clay materials and (25 wt.%) CaCO3 using an extrusion technique, which enabled the production of tubular supports. The CaCO3 is responsible for creating the pores in the samples during heat treatment due to the evolution of CO2 gas. Some characteristics of the supports were evaluated using X-ray diffraction, which identified quartz, gehlenite, sillimanite, H-bearing aluminous stishovite, and wollastonite. The support treated at 1000°C displayed significant mechanical properties (flexural strength, 11.58 MPa, measured using three-point bending tests) compared with supports treated at other temperatures. Moreover, the support sintered at 1000°C had an estimated permeability factor of 1052 L/h m2.bar after performing both time- and pressure-dependent flux measurements. Such properties make it possible to use these supports as multi-scale filtration membranes for purification and filtration applications after performing a standard filtration application on dirty water, resulting in a significant difference in terms of turbidity and waste content.

The European Green Deal (EGD) provides a strategic framework for the European Union’s (EU) transition to climate neutrality by 2050. Yet, limited integration of socio-economic dimensions may hinder its long-term success and fairness. This study investigates the indirect impacts of socio-economic factors on EGD performance by constructing a Green Deal Performance Index (GDPI) using a multi-criteria decision-making approach for 22 EU countries over 2010–2020. We then apply an instrumental variable regression approach to estimate how emissions, shaped by structural socio-economic conditions, affect the GDPI. Our results show that the negative impact of emissions is nearly 47 times larger when socio-economic dynamics are ignored. These findings underscore the necessity of inclusive policymaking for achieving carbon neutrality, contributing to discussions on ensuring a just transition by highlighting the critical role of socio-economic dynamics. We also present implications for policymakers developing fair and equitable strategies promoting sustainability and social justice in this context.