Crystal-chemical features of high-calcium and hypercalcium eudialyte-group minerals (EGMs) from a carbonatite-related rock of the Tamazeght peralkaline complex, High Atlas Mountains, Morocco were studied using electron probe microanalysis, single-crystal X-ray structure analysis, infrared and Raman spectroscopy. The major components of the host rock are calcite, fluorite and EGMs; aegirine–augite is present in subordinate amounts. The specific features of the studied EGMs are chemical heterogeneity, a complex zoning, reaction zones around calcite and apatite inclusions, Na- and Cl-deficiency, high contents of Ca, Mn, REE, Nb, carbonate and H-bearing groups, positive correlation between Nb and Mn and negative correlations between the pairs Fe–Mn and Zr–Mn. These features confirm previous assumptions about the role of infiltration of carbonatite fluid rich in Ca, Mn, REE, Nb, CO2 and H2O and a depletion of Cl in the remaining fluid after the crystallization of sodalite at the expense of nepheline in the formation of carbonatite-related rocks of the Tamazeght complex. The crystal structure of a single-crystal fragment extracted from the Nb-rich zone refined to R1 = 0.0335 has shown a high degree of ordering of Na, REE and H3O+ and the dominance of Fe3+ at the M2 site with five-fold coordination. The composition of EGMs from the reaction zones around calcite and apatite inclusions corresponds to Mn-dominant (with Mn > Fe at the M2 site) analogue of feklichevite with the simplified formula Ca3(Na,K)9(H3O)3Ca6Zr3(Mn2+,Fe3+,Zr)3NbSi(Si24O72)(OH,H2O)5(F,Cl)2/3(CO3)1/3.

Identifying use-related residues from stone artefacts has become increasingly important in determining starchy plant exploitation over time and in different locales. Standard methods for processing residues samples are widely available but there is no clear consensus on suitable methods for attributing unknown starch grains to known plant taxa. We revisit the case study of a flaked stone artefact (K/76/S29B) recovered from Phase 1 (c. 10,000 ka) at Kuk Swamp in Papua New Guinea (PNG). Starch grains from taro (Colocasia esculenta) were identified in the residue extraction, but there were other grains that could not be attributed a plant origin at that time. The new analysis applied robust statistical methods, categorial attributes and expert input. In addition to C. esculenta, kudzu bean (Pueraria montana var. lobata) was identified, representing the earliest use of kudzu bean in the PNG highlands. Importantly, we also determined that starch grains from C. esculenta and Dioscorea esculenta are morphologically indistinguishable. We turned to other attributes of potential contributing plant taxa in determining distinguishing features: habit/growing requirements; the sedimentary context of the archaeological find; and environmental settings. Cultural use of both plants, artefacts and artefact technologies can be critical elements in confident identification outcomes, as exemplified here.

Refreezing is a critical component of the mass balance of glaciers in Svalbard, yet the processes and changes under a warming climate are not fully understood. Here, we investigate changes in firn properties of the Austfonna ice cap, Svalbard, using a combination of observations and model simulations. We analyze firn stratigraphy and density from five newly retrieved and 11 previously retrieved firn cores, collected at elevations ranging from 506 m a.s.l. to 791 m a.s.l. between 1958 and 2022. All cores exhibit frequent ice layers that indicate persistent refreezing of meltwater; however, no ice slabs (layers exceeding 1 m) were observed. A 13-year-long firn temperature time series from a site near the summit (773 m a.s.l.) shows that annual water percolation reaches depths of 7 m to over 13 m. A notable transition in the firn thermal regime occurred in 2013, transitioning from cold to temperate conditions above the firn-ice interface despite the seasonal cooling occurring in the upper firn layers. Simulations using the CryoGrid community model from 2009 to 2022 corroborate this thermal shift and suggest the development of a firn aquifer multiple times since 2013, with increasing duration and thickness over time.

Miocene lacustrine clay deposits formed in the Şile region of Türkiye rest unconformably on Cretaceous andesite, basaltic andesite, basalts and rare dacites. Factors controlling the genesis of this sequence include: (1) sediment provenance, (2) tectonic uplift and climatic regimes during syn- and post-depositional times, (3) burial diagenesis and (4) changes from surface weathering alterations (i.e. oxidation and hydrolysis reactions) in the critical zone. Clay minerals are dominated by kaolinite and illite, with their relative abundances varying in relation to the proximity of coal seams, stratigraphic sequence and in an overlying sand-rich fluvial deposit. Variations in the mineral abundances reveals cyclothem-like sequences with patterns of fining upwards (i.e. increasing clay mineral abundance) capped by thin coal seams. The Clay Mineral Alteration Index values for the Şile clay sequence indicate a slight trend of decreasing chemical weathering intensity up-section, which is consistent with regional geological data for terrain uplifting and a drying climate during the Miocene. Critical zone processes have modified the mineral and chemical assemblages, as evidenced by the appearance of iron oxides putatively formed from recent oxidation of the ferrous minerals siderite and pyrite, which are not found in the upper sections. Taken together, the evidence indicates that the clay minerals are derived from a combination of prior weathering of basement rocks, diagenesis after deposition and modern critical-zone weathering. The degree of each process is dependent on depositional history, stratigraphic position and depth below the land surface, all under the changing influences of tectonic uplift and regional climate. The Şile deposits provide an economical clay resource that could be important to the ceramics industry of Türkiye.

Every private rural property in Brazil must maintain a percentage of its area with conserved native vegetation, establishing a legal reserve area (LRA). This percentage is defined by the Brazilian Federal Law on Protection of Native Vegetation and is 20–80% of the rural property, depending on the political boundary and vegetation formation. However, the Environmental Code of Mato Grosso stipulates that vegetation type determines the LRA percentage in the state of Mato Grosso, considering both vegetation formation and floristic composition. In addition, the state adopts a coarse-scale vegetation map as a reference, despite the existence of a more accurate official map. In this study, we calculated the impacts of these provisions by combining legal interpretation, spatial analysis and ecological reasoning, in accordance with the scientific concepts of ecology, and intersecting official maps from the State Environmental Agency and the Brazilian Institute of Geography and Statistics, at the scales of 1:1 000 000 and 1:250 000, respectively. A total of 9 045 065 ha could have their LRA requirement reduced from 80% to 35% under Mato Grosso’s legislation, potentially authorizing deforestation in the Amazon, Cerrado and Pantanal, in apparent contradiction to federal law. These findings highlight that issues related to the concepts, classifications and mapping scales for defining native vegetation have significant implications for biodiversity conservation.

Accurate knowledge of basal topography is required for numerical modelling efforts to predict how Earth’s ice sheets will respond to continued warming. The widely used BedMachine v3 dataset has limitations with respect to its use in modelling studies, particularly in estimating uncertainties. Machine learning approaches offer promise in addressing this gap, with quantile regression forests (QRFs) especially suited to geospatial data. Here, we apply a novel QRF approach to map the basal topography of Greenland’s ice sheet using airborne radio echo sounding (RES) data. Compared to BedMachine, our model reduces the root-mean-squared-error of ice depth predictions by 18%, from 232 to 190 m. It also significantly improves uncertainty calibration: 89.8% of new observations fall within our 90% prediction interval, versus 68% for BedMachine. The QRF model achieves a lower continuous ranked probability score (92 m vs. 130 m), indicating improved balance between accuracy and uncertainty. Our volume estimate for the Greenland ice sheet is 0.7% higher than BedMachine’s, though we emphasise differences in the predicted shape of subglacial features like outlet glacier troughs. This approach offers a computationally efficient, accessible method for deriving subglacial topography from RES data, while providing better-calibrated uncertainty estimates than existing models.

The Eastern Ghats Belt (EGB) has been extensively studied by the geoscientific community; however, this communication reports unique mineral assemblages that have not been documented previously. This study documents the occurrence of sapphirine, spinel, orthopyroxene, sodic-gedrite, calcic-amphibole, biotite and plagioclase assemblage indicating in ultrahigh temperature (UHT) metamorphic conditions. The significance of this study lies in the peculiarity of sapphirine being present within anorthite matrix which has been reported for the first time from the Indian subcontinent. The studied assemblage has been correlated with the more or less similar assemblage of rock called ‘Sakenites’ reported from southern Madagascar to correlate the most probable source rock ‘anorthosites’ that underwent metamorphic transformations and led to the unique UHT mineral assemblage. The Na-rich gedrite identified within the assemblage represents a relict mineral indicative of high-grade amphibolite-facies metamorphism. The derived pressure–temperature (P-T) trajectory reveals a decompression path with almost uniformly decreasing P-T conditions in contrast to the commonly reported isothermal decompression (ITD) path from various other domains and provinces of the EGB. The corresponding retrograde assemblage has been recalibrated by the sequential removal of sapphirine and corroborated with T-X (H2O) constraints.

The analyzed EMP U-Th-Pb monazite chemical age constraints suggest mesoproterozoic to neoproterozoic episodes corresponding to a pair of ∼959 Ma and ∼846 Ma thermal events. These metamorphic events have been correlated to reconstructing the Rodinian supercontinent at ∼959 Ma and the initiation of its subsequent break-up at ∼846 Ma.

Submarine glacier melt rates of the Greenland Ice Sheet remain a major uncertainty in climate model projections of future sea level rise. Development of submarine melt parameterizations has to a high degree relied on ocean circulation modelling of glacial fjords, designed to quantify effects such as ocean thermal forcing and fjord–glacier geometry. Greenlandic fjords are relatively narrow, and it is frequently assumed that across-fjord flow variations are small enough to allow marine melt to be quantified with two-dimensional ocean-circulation models. Here, we present three-dimensional model simulations showing that the interplay between fjord–glacier geometry, side wall friction, and Earth’s rotation makes the circulation in ice-shelf cavities three-dimensional even in narrow fjords. Remarkably, we find that Earth’s rotation changes the flow pattern in the cavity below the ice shelf, leading to a decrease in the marine melt on a 10 km wide ice shelf by a factor of five compared to a non-rotating simulation. Our study prompts using three-dimensional model configurations of Greenlandic fjords.

Monitoring wildlife populations in vast, remote landscapes poses significant challenges for conservation and management, particularly when studying elusive species that range across inaccessible terrain. Traditional survey methods often prove impractical or insufficient in such environments, necessitating innovative technological solutions. This study evaluates the effectiveness of deep learning for automated Bactrian camel detection in drone imagery across the complex desert terrain of the Gobi Desert of Mongolia. Using YOLOv8 and a dataset of 1479 high-resolution drone-captured images of Bactrian camels, we developed and validated an automated detection system. Our model demonstrated strong detection performance with high precision and recall values across different environmental conditions. Scale-aware analysis revealed distinct performance patterns between medium- and small-scale detections, informing optimal drone flight parameters. The system maintained consistent processing efficiency across various batch sizes while preserving detection quality. These findings advance conservation monitoring capabilities for Bactrian camels and other wildlife in remote ecosystems, providing wildlife managers with an efficient tool to track population dynamics and inform conservation strategies in expansive, difficult-to-access habitats.

Subglacial drainage models, often motivated by the relationship between hydrology and ice flow, sensitively depend on numerous unconstrained parameters. We explore using borehole water-pressure time series to calibrate the uncertain parameters of a popular subglacial drainage model, taking a Bayesian perspective to quantify the uncertainty in parameter estimates and in the calibrated model predictions. To reduce the computation time associated with Markov Chain Monte Carlo sampling, we construct a fast Gaussian process emulator to stand in for the subglacial drainage model. We first carry out a calibration experiment using synthetic observations consisting of model simulations with hidden parameter values as a demonstration of the method. Using real borehole water pressures measured in western Greenland, we find meaningful constraints on four of the eight model parameters and a factor-of-three reduction in uncertainty of the calibrated model predictions. These experiments illustrate Gaussian process-based Bayesian inference as a useful tool for calibration and uncertainty quantification of complex glaciological models using field data. However, significant differences between the calibrated model and the borehole data suggest that structural limitations of the model, rather than poorly constrained parameters or computational cost, remain the most important constraint on subglacial drainage modelling.