Rare Earth Elements (REEs) are essential for green energy technologies and defense systems, yet global supply chains remain concentrated in China. This has intensified geopolitical competition for alternative sources, positioning the Arctic as a strategic frontier, as retreating ice exposes mineral deposits. A comprehensive discourse analysis of strategic documents, scholarly literature, and media sources from 2010 to 2025 reveals a dramatic shift from geological characterization and economic speculation to urgent securitization and strategic alliance formation. Academic research has evolved from establishing natural baselines to governance and social conflict analysis. Media coverage of REE in the Arctic peaked in 2025, with rising emphasis on governance, sovereignty, geopolitics, and Greenland’s strategic position. Critical gaps persist in addressing Indigenous rights, holistic impact assessments, and Arctic-specific innovation. Sustainable Arctic REE development requires integrated frameworks that balance geopolitical imperatives with environmental protection and Indigenous self-determination, preventing the region from becoming a sacrifice zone for global decarbonization.

The annelid genus Diopatra is a well-known example of marine ecosystem engineering, as it creates tubes in coastal sediments all around the world. In the Amazon coast, this annelid is common in intertidal estuarine areas and protected beaches. However, there are no data for the Amazon coast regarding studies on the meiofauna associated with Diopatra sp. tubes. Therefore, the present study characterized, for the first time, the meiofauna community found on a muddy-sandy tidal flat of the Amazon coast in areas with and without the presence of Diopatra sp. tubes. Samples were collected in February 2014 in two different areas: (1) an area in which Diopatra sp. tubes were present, and (2) an area without tubes. A total of 13 major meiofaunal groups were found, with Nematoda as the dominant group. Overall, a significant increase in meiofauna density and richness of the meiofauna was observed in the area with the presence of Diopatra sp. tubes. While no large aggregations of Diopatra sp. tubes were observed in the study region, the presence of even a single tube had significant effects on the environmental conditions available to the meiofauna community. The present findings add knowledge about the presence of the bioconstructor in coastal areas and reinforce the role of tube-building polychaetes as ecosystem engineers.

This study presents a framework that combines Bayesian inference with reinforcement learning to guide drone-based sampling for methane source estimation. Synthetic gas concentration and wind observations are generated using a calibrated model derived from real-world drone measurements, providing a more representative testbed that captures atmospheric boundary layer variability. We compare three path planning strategies—preplanned, myopic (short-sighted), and non-myopic (long-term)—and find that non-myopic policies trained via deep reinforcement learning consistently yield more precise and accurate estimates of both source location and emission rate. We further investigate centralized multi-agent collaboration and observe comparable performance to independent agents in the tested single-source scenario. Our results suggest that effective source term estimation depends on correctly identifying the plume and obtaining low-noise concentration measurements within it. Precise localization further requires sampling in close proximity to the source, including slightly upwind. In more complex environments with multiple emission sources, multi-agent systems may offer advantages by enabling individual drones to specialize in tracking distinct plumes. These findings support the development of intelligent, data-driven sampling strategies for drone-based environmental monitoring, with potential applications in climate monitoring, emission inventories, and regulatory compliance.

Paleolake coring initiatives result in large datasets from various proxies taken at different resolutions, ranging from continuous scans to samples collected at coarser intervals. Higher-resolution data (e.g., core-scan X-ray fluorescence [XRF]) can detect short-duration changes in the paleolake and help identify unit boundaries with precision; however, interpreting the causes of such changes may require sampling and more intensive laboratory analysis like X-ray diffraction (XRD). This study applies a published wide and deep learning model, developed for the Olduvai Gorge Coring Project (OGCP) 2014 cores from the Pleistocene Olduvai basin, Tanzania, to reconstruct the mineral assemblages from saline-alkaline paleolake Olduvai using core-scan XRF data and core lithology. A classification model (predicting mineral presence or absence) and a regression model (predicting relative abundances of minerals) yielded predictions for two OGCP cores (2A and 3A), which were compared with published XRD mineral data and detailed core sedimentological descriptions. The models were excellent at identifying dolomite-rich layers, carbonate-rich intervals, intervals of sandstone within claystone, and altered tuffs within claystone and at predicting whether illitic or smectitic clays dominate. The models struggled with less-altered tuffs and with zeolites in non-tuff sediments, especially when XRD identified chabazite and erionite (rather than phillipsite) as the dominant, non-analcime zeolite.

La Viña rock shelter is a relevant archaeological site for understanding the late Middle and Upper Palaeolithic cultural development in northern Iberia as evidenced by the Mousterian, Aurignacian, Gravettian, Solutrean and Magdalenian bone and lithic industries, parietal engravings and human subsistence remains recovered during the 1980s excavations by J. Fortea in the western and central excavation areas. This paper aims to present 16 new radiocarbon dates, which are added to the previous radiocarbon dates obtained, using different analytical methods on bone and charcoal. These are now 57 dates in total. Bayesian models have been applied to assess and discern the chronology of the archaeological sequence in each sector of the rock shelter. The results provide details on the chronostratigraphy of each excavation area, documenting the duration of the different technocultural phases and confirming in-site postdepositional events.

Recent palaeobiological studies have emphasized the need for interpretations of the fossil record to consider spatial changes in environmental conditions (e.g. topography, climate). Establishing the role the environment plays in determining the distributions of extinct and existing organisms is complicated by biological evolution. Using available observations to ‘see through’ the randomness of biological evolution to determine contributions from environmental change is not trivial because of the sparsity of the fossil record, lack of precise information about rates of evolution, and because we obviously cannot physically re-run the evolutionary history that resulted in modern biodiversity or the fossil record. To address these issues, we establish scales and scenarios in which spatial environmental change is manifested in records of the number of species in a given area (richness) generated by eco-evolutionary simulation. Evolutionary processes that are likely to be random on the timescales of environmental change are included. Signals of environmental change that are likely to be hidden by the effects of ‘noisy’ evolutionary processes and those likely to emerge are identified. The ‘experiment of life’ is simulated many times, producing statistical insights. Results show that the spatial rate of environmental change is strongly correlated with species richness when the ability of organisms to disperse is high. Interaction between scale, dispersal and environmental structure is shown to determine both statistical and spatial distributions of richness. As a proof-of-concept, we compare predictions to bird species richness. The results emphasize the need to consider the randomness of evolution when interpreting the observations of extinct or present life on Earth.

The present account describes a new species of alpheid shrimp, Alpheus madhusoodanai sp. nov., belonging to the brevirostris group, collected from the Cochin estuary, the south west coast of India. This represents the first species of alpheid shrimps described from the estuary. The morphological and molecular characteristics of the new species are compared with those of its closely related congeners. The newly described species is separated from its morphological congener A. rapax, by its wider major chela and longer merus of the first cheliped. Molecular data also confirmed the delimitation of A. rapax with A. madhusoodanai sp. nov. Habitat and distribution details are also discussed, highlighting the potential for further taxonomic exploration in the Cochin estuary and the importance in uncovering its hidden biodiversity.