Strong Variations Research Articles

Methodological insights into soil elemental nickel in typical Karst areas: comprehensive analysis of geochemical characteristics, source determination, and influencing factors.

Excessive levels of Nickel in the soil can compromise the security of agricultural products, posing a threat to health of human beings; therefore, the repair and treatment of Nickel exceeding the standard levels in soil are particularly critical. Although it is crucial that the potential restoration of Nickel in ensuring the security of both soil and farm produce within karst regions., few studies have been conducted on the potential restoration of large-scale Nickel-contaminated soils. In this study, the soil in Wuming, Guangxi, a typical karst area, was comprehensively studied. 12,547 surface soil samples, 134 deep soil samples and 60 soil profiles were collected systematically. The results showed that the Nickel background value of the surface soil was 34.9mg/kg, indicating strong background characteristics and high variability. Principal component analysis showed that soil Nickel was primarily derived from natural sources in the geological background and partly derived from agricultural sources. Analysis of variance showed that the Nickel content of the soil was affected by the parent rock, soil type, soil use type, and topography. In addition, the distribution of Nickel in the soil profile increased exponentially with depth. Therefore, the exponential model and multiple integrals were used to derive the formula for the Nickel potential restoration amount at different depth ranges, and the potential restoration amount of soil Nickel was calculated based on different parent material, soil, and land use types. The formula is reasonable and representative and can provide a theoretical basis for the remediation and treatment of Nickel-polluted soil in karst areas.

Inferring the distribution of the ionising photon escape fraction

The escape fraction of ionising photons from galaxies ($f_ esc $) is a key parameter for understanding how intergalactic hydrogen became reionised, but it remains mostly unconstrained. Measurements have been limited to the average value in galaxy ensembles and to handfuls of individual detections. To help understand which mechanisms govern ionising photon escape, here we infer the distribution of $f_ esc We developed a hierarchical Bayesian inference technique to estimate the population distribution of $f_ esc $ from the ratio of Lyman continuum to non-ionising UV flux measured from broadband photometry. We applied it to a sample of 148 $z 3.5$ star-forming galaxies from the VANDELS spectroscopic survey. We explored four physically motivated distributions: constant, log-normal, exponential, and bimodal, and recovered $ f_ esc for most models. We find the observations are best described by an exponential $f_ esc $ distribution with scale factor $ $. This indicates most galaxies in our sample exhibit very low escape fractions, while predicting substantial ionising photon leakage for only a few galaxies, implying a range of optical depths in the interstellar medium and/or time variability in ionising photon escape. We rule out a bimodal distribution at high significance, indicating that a purely bimodal model of ionising photon escape (due to very strong sightline and/or time variability) is not favoured. We compare our recovered exponential distribution with the SPHINX simulations and find that, while the simulation also predicts an exponential distribution, it significantly underpredicts our inferred mean. The distribution of $f_ esc $ can be a vital test for simulations in understanding ionising photon leakage, and is important to consider to gain a complete picture of reionisation.

Opposite Trends in the Northern Hemisphere Stratosphere Between Mid‐Winter and Early Spring Linked to Surface Temperature Anomalies

AbstractTrends in the coupled stratosphere‐troposphere system during the 1979–2022 period are investigated in the Northern Hemisphere using reanalysis datasets. More upward planetary wave propagation in December is shown to precede the deceleration of the stratospheric polar vortex in January. This deceleration prevents the waves from continuing to propagate upward in February and favors an acceleration of the stratospheric polar vortex in March. This is associated with an increased Northern Hemisphere annular mode in March in the stratosphere and the troposphere. Trends show a moderate significance level because of strong interannual variability. Recent seasons whose anomalies project onto the trends are those for which wave‐1 anomaly constructively interferes with wave‐1 climatology in December, which occurs when there is warming in an area extending from Eastern Canada to Greenland and slight cooling over Eurasia. It shows the potential for predicting the springtime stratospheric polar vortex from wintertime wave‐1 anomalies.

Strengthening of the Equatorial Pacific Upper‐Ocean Circulation Over the Past Three Decades

AbstractThirty years (1993–2022) of concurrent satellite and in‐situ observations show a long‐term strengthening of the equatorial Pacific upper‐ocean circulation. Enhanced southeasterly and cross‐equatorial winds have caused an annual mean, basin‐wide acceleration of the equatorial westward near‐surface currents by ∼20% and an acceleration of poleward flow north (south) of the equator by ∼60% (∼20%). Additional moored velocity data reveal a deepening of the Equatorial Undercurrent (EUC) core at 170°W and significant shoaling at 140°W and 110°W, but no significant changes in EUC core velocity. The strongest subsurface zonal velocity trends are observed above the EUC core in the central to eastern Pacific and occur before and after the seasonal maximum of EUC core velocity, causing enhanced upper‐ocean vertical current shear. Consistent with trends of the 20°C isotherm depth along the equatorial Pacific, a significant basin‐wide steepening of the equatorial thermocline is observed. Both the accelerating equatorial current system and the enhanced thermocline slope are consistent with an observed steepening of the zonal sea surface height gradient due to increased wind‐driven westward mass transport at the surface. During February‐March, both surface and subsurface currents along the equator show eastward velocity trends, in contrast to westward near‐surface current trends during the remainder of the year. The trend reversal is attributed to both a long‐term shift in equatorial Kelvin wave activity and to the impact of strong interannual variability due to El Niño Southern Oscillation and other modes of natural variability on decadal to multidecadal time scales.

A wiggling filamentary jet at the origin of the blazar multi-wavelength behaviour

Blazars are beamed active galactic nuclei (AGNs) known for their strong multi-wavelength variability on timescales ranging from years down to minutes. Many different models have been proposed to explain this variability. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions. We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019--2022, together with radio data from the WEBT and other teams, and gamma -ray data from the Fermi satellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical and gamma -ray brightness maxima. The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, and gamma -ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. The gamma -ray emitting region is found to be co-spatial with the optical one, and the analysis of the gamma -optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons. We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability.

Improved nitrogen fertilizer management reduces nitrous oxide emissions in a northern Prairie cropland.

Arable croplands are a significant source of nitrous oxide (N2O) emissions, largely due to nitrogen (N) fertilizer applications to support crop production. Nevertheless, there is limited research on the N2O dynamics from canola-wheat rotations in the semi-arid northern Prairies, an important agricultural region. Here, we present micrometeorological N2O fluxes measured from January 2021 to April 2024 in Saskatchewan, Canada, to evaluate the impact of N fertilizer management on the year-round N2O emissions from a canola-wheat rotation. A combination of two 4R (Right Source, Right Rate, Right Time, Right Place) N management practices - a reduced N rate and an enhanced efficiency N fertilizer source - was compared to common fertilizer management practices for the region. Two periods at high risk for N2O flux events were identified, after N fertilizer applications and the following spring thaw, with the magnitude of emissions varying over the multi-year period. As for cumulative emissions, the growing season (GS) N2O emissions were 50 % of annual emissions, presenting an opportunity to mitigate N2O emissions through improved N fertilizer management. Indeed, the improved 4R N management reduced N2O emissions by 57 % over the entire study period without impacting yields. The reduction in GS N2O emissions resulted from the 4R N management lowering mean N2O flux at times of high WFPS (>50 %). The non-growing season (NGS) N2O accounted for 11-67 % of annual emissions. Fall soil nitrate levels were a strong explanatory variable of NGS emissions (r2 = 0.69, r2 = 0.39), but the rate of change and magnitude of NGS emissions depended on thawing conditions - lower for drier thaws, higher for wetter thaws. Ultimately, better N fertilizer management reduces cumulative N2O emissions from cropping systems when practiced for several years.

Seasonality in cave dripwater and air properties – implications for speleothem palaeoclimatology, Nova Grgosova Cave (Croatia)

Due to the wealth of climate-sensitive properties, speleothems have been propelled into prominence as one of the most powerful continental archives of past climate changes. However, the multitude of processes that operate in the unsaturated karst zone and in the cave atmosphere can make palaeoclimate interpretations of the speleothem proxies challenging and site specific. Hence, to better understand the climate-proxy relationship, cave monitoring studies are usually undertaken. Here, we present the first results of an ongoing cave monitoring study in the Nova Grgosova Cave in Croatia covering an eighteen-month long monitoring period. The driving mechanisms for Mg/Ca and Sr/Ca variability in dripwater samples that feed ten stalagmites are discussed. The results reveal high variability in infiltration among the monitored sites as well as strong seasonal variability in cave air carbon dioxide (CO2) concentrations. A strong positive correlation between dripwater Mg/Ca and Sr/Ca suggests that prior calcite precipitation (PCP) is taking place at this site affecting the chemical composition of dripwater. Principal component analysis furthermore reveals that dripwater Mg/Ca and Sr/Ca are in strong negative correlation with cave air CO2 concentrations, while there is a weak correlation with dripwater quantity. Cave ventilation is a primary process leading to the PCP at the Nova Grgosova Cave. The seasonality revealed in this study suggests the possibility that the Mg/Ca and Sr/Ca ratio in the speleothems from this cave site can be used to aid seasonal reconstructions of past climate conditions in central Croatia and beyond.

Strong Subseasonal Variability of Oxic Methane Production Challenges Methane Budgeting in Freshwater Lakes.

Methane (CH4) accumulation in the well-oxygenated lake epilimnion enhances the diffusive atmospheric CH4 emission. Both lateral transport and in situ oxic methane production (OMP) have been suggested as potential sources. While the latter has been recently supported by increasing evidence, quantifying the exact contribution of OMP to atmospheric emissions remains challenging. Based on a large high-resolution field data set collected during 2019-2020 in the deep stratified Lake Stechlin and on three-dimensional hydrodynamic modeling, we improved existing CH4 budgets by resolving each component of the mass balance model at a seasonal scale and therefore better constrained the residual OMP. All terms in our model showed a large temporal variability at scales from intraday to seasonal, and the modeled OMP was most sensitive to the surface CH4 flux estimates. Future efforts are needed to reduce the uncertainties in estimating OMP rates using the mass balance approach by increasing the frequency of atmospheric CH4 flux measurements.

Geoelectric fields and geomagnetically induced currents during the April 23–24, 2023 geomagnetic storm

We present a study on the dynamical variations of geoelectric fields E during the intense geomagnetic storm of April 23–24, 2023. The storm is caused by the interplanetary counterpart of a coronal mass ejection erupted from the Sun in association with an M1.7 X-ray flare. The GeoElectric Dynamic Mapping (GEDMap) code is applied to develop spatial E maps using magnetometer data from 29 observatories distributed across northern Europe. The code has been applied during local nighttime and morningtime intense substorms which occurred during the storm main phase. The maps show intensifications and strong variability of the E-fields during the substorm events. In particular, the morningtime event is associated with a significant variability in the E-field direction. Using the computed E-fields, we determined geomagnetically induced currents (GICs) at the sub-auroral station Mäntsälä. The modeled GIC values exhibit significant correlation (correlation coefficients r=0.73−0.76\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$r=0.73-0.76$$\\end{document}) with the observed values. The performed E-field mapping provides a basis for the further determination of GICs in selected locations not covered by magnetometers and can be useful in understanding the GIC variability during magnetic storms and substorms.

Venous thromboembolism and ovarian cancer risk: a Mendelian randomized study

IntroductionA potential link between venous thromboembolism and the risk of ovarian cancer has been identified in clinical practice. However, it is unclear whether there is a causal relationship between the two. In this study, we applied a univariate two-sample Mendelian randomization method to explain the possible link between venous thromboembolism and ovarian cancer pathogenesis at the genetic level, and pointed out that lipid metabolism and ovarian cancer pathogenesis have innovative basic experimental directions.ObjectiveThis study explored the causal effect between a history of venous thromboembolism and the risk of ovarian cancer.MethodsGenome-Wide Association Study (GWAS) data of venous thromboembolism patients (n = 9176) of the same ethnicity were selected as study exposures, and GWAS data of ovarian cancer patients (n = 1218) of the same ethnicity were selected as study exposures. In this study, univariate two-sample Mendelian randomization analysis (UVMR) was performed separately using inverse variance weighted (IVW), MR-Egger regression, and weighted median (WM) to assess causal effects. In this study, Cochran’s Q test, MR-Egger regression intercept term, MR-PRESSO, and leave-one-out method were used for sensitivity analysis to assess the stability and reliability of the results.ResultsThe GWAS data screened in this study were all European ethnicity data. In this study, we found that genetically predicted history of venous thromboembolism was associated with an upward trend in ovarian cancer incidence, and the results of Weighted median, Simple mode, Weighted mode, and MR Egger showed a similar trend (OR = 1.0006, 95% CI: 1.00007–1.0013, p < 0.05). There was no heterogeneity of results (p = 0.18) and no horizontal pleiotropy (p = 0.77). The instrumental variables selected for venous thromboembolism in this study were all strong instrumental variables (F = 669.7). The results of the sensitivity analysis remained consistent.ConclusionThe results of this study indicate that patients with a history of venous thromboembolism are at increased risk of developing ovarian cancer and point to possible associations between lipid metabolism genes, such as CYP4V2, and the development of ovarian cancer, which provide interesting directions for further basic research.

Forgotten treasures in the HST/FOC UV imaging polarimetric archives of active galactic nuclei. III. Five years monitoring of M87

The active galactic nucleus within M87, a giant elliptical galaxy, is responsible for one of the closest kiloparsec-scale relativistic jets to Earth. It is thus a perfect target for spatially resolved observations. This one-sided jet has been extensively observed at almost all wavelengths, with almost all techniques. Among many other discoveries, it was found that the optical emission is more concentrated in the knots and along the center line of the jet, in comparison to, for example, the radio emission. A remaining question relates to what we can learn from its polarized counterpart. We unearthed unpublished polarization maps taken with the Faint Object Camera (FOC) aboard the Hubble Space Telescope (HST), obtained between 1995 and 1999. At a rate of one observation per year, we can follow the evolution of the polarized flux knots in the jet. We can thus constrain the timescale of variation in the magnetic field up to a spatial resolution of one tenth of an arcsecond (sim 11.5 pc). After coherently reducing the five observations using the same methodology presented in the first paper of this series, the analysis of polarized maps from POS 1 (base of the jet) and POS 3 (end of the jet) reveals significant temporal and spatial dynamics in the jet's magnetic field morphology. Despite minimal changes in the overall intensity structure, notable fluctuations in polarization degrees and angles are detected across various knots and inter-knot regions. In addition, the emission and polarization characteristics of M87's jet differ significantly between POS1 and POS3. POS1 shows a more collimated jet with strong variability in polarization, while POS3 reveals a thicker structure, a quasi-absence of variability, and complex magnetic field interactions. This suggests that the jet may have coaxial structures with distinct kinetic properties. Theoretical models like the jet-in-jet scenario, featuring double-helical magnetic flux ropes, help to explain these observations and indicate a strong density contrast and higher speeds in the inner jet. Our temporal analysis demonstrates the importance of high-spatial-resolution polarization mapping in understanding jets' polarization properties and overall dynamics, especially if such maps are taken at different wavelengths (ultraviolet and radio).

Analysing the accessibility of a selected southern Baltic Sea location with relevance to conducting surveys

The article presents the accessibility conditions for carrying out research work for an exemplary site in the southern Baltic Sea region. The basic parameter of the state of the marine environment was the significant wave height determined at a frequency of one hour based on the ERA 5 model data covering the period between 1940 and 2022. A statistical analysis of the variability of this height on a monthly basis, taking into account its conversion into the time of potential availability in conditions enabling research, showed its strong seasonal variability in the form of differences in the number of hours that can be used for operating purposes. This number, depending on the research vessel capabilities, may even be an order of magnitude higher in the summer months than in winter. Additionally, it was found that the variability of the significant wave height has not changed substantially over the last 82 years.

Drivers of growth and decay of Sargassum in the Tropical Atlantic: A Lagrangian approach

The proliferation of Sargassum in the Tropical Atlantic has occurred almost every year since 2011, but a strong variability of biomass is observed among years. Essential knowledge about the drivers of Sargassum growth and decay is still lacking to explain this interannual variability. Benefiting from accurate basin scale Sargassum detections provided by remote sensing, and from physical and biogeochemical ocean simulations, we developed a Lagrangian drift-growth model to simulate Sargassum distribution over the period 2016–2020. The resulting trajectories and biomass time series of Sargassum aggregates were analyzed to highlight the main limiting factors of growth and decay. The nitrogen and phosphorous concentrations are found to be weakly restrictive compared to physical limiting factors, especially the temperature. In particular, the warm waters found off northern Brazil appear to be instrumental in triggering the end of seasonal growth of Sargassum. The timing of the seasonal warming of this region strongly impacts the quantities of Sargassum simulated each year. This suggests that this region should be monitored to anticipate the development of Sargassum and resulting strandings.

Cold-water coral mortality under ocean warming is associated with pathogenic bacteria

Cold-water corals form vast reefs that are highly valuable habitats for diverse deep-sea communities. However, as the deep ocean is warming, it is essential to assess the resilience of cold-water corals to future conditions. The effects of elevated temperatures on the cold-water coral Lophelia pertusa (now named Desmophyllum pertusum) from the north-east Atlantic Ocean were experimentally investigated at the holobiont level, the coral host, and its microbiome. We show that at temperature increases of + 3 and + 5 °C, L. pertusa exhibits significant mortality concomitant with changes in its microbiome composition. In addition, a metagenomic approach revealed the presence of gene markers for bacterial virulence factors suggesting that coral death was due to infection by pathogenic bacteria. Interestingly, different coral colonies had different survival rates and, colony-specific microbiome signatures, indicating strong colony-specific variability in their response to warming waters. These results suggest that L. pertusa can only survive a long-term temperature increase of < 3 °C. Therefore, regional variations in deep-sea temperature increase should be considered in future estimates of the global distribution of cold-water corals.

Bioinformatics Analysis and Spatiotemporal Distribution of the fliC Gene and Its Protein Isolated from Escherichia coli-Infected Patients in Eastern Algeria.

The fliC locus in Escherichia coli primarily encodes flagellar (H) antigens. Exploring fliC sequence diversity will shed light on the mechanisms of bacterial pathogenicity. This study examined the presence of fliC mutant strains of E. coli in infected patients from different age groups, sexes and sample types in eastern Algerian provinces over a span of 2 years. This retrospective, cross-sectional study involved three provinces in eastern Algeria: i) Bordj Bou Arreridj, ii) Setif and iii) Batna. A total of 75 E. coli isolates were obtained from the University State Hospital Centre. Two types of analyses were conducted: i) a bioinformatics analysis of the protein sequences translated from the fliC genes, specifically the fliC flagellar sequences and ii) a multifactorial statistical analysis (multiple correspondence analysis [MCA]) of the population of infected patients, considering various parameters. The fliC protein sequences were aligned using the Multiple Alignment using Fast Fourier Transform (MAFFT) programme. The alignment results were then visualised using the MView programme. Finally, a phylogenetic tree was constructed using the maximum likelihood algorithm in MEGA 11 software. Bioinformatics analysis highlighted the strong conservation of the structures of the fliC protein sequences, especially at the two N- and C-terminal ends, and strong variability in the central zone. This remarkable fliC intersequence similarity is corroborated by the presence of protein motifs identified in the PROSITE protein motif database. fliC mutations in E. coli were not detected in the clinical samples of patients from hospitals in the three Algerian Provinces. Our analysis revealed that all the samples exhibited characteristics of wild-type virulent bacteria without mutations. A multicentre study is warranted for epidemiological surveillance of fliC mutant strains for future preventive measures.

Tidal levels significantly change bacterial community composition in a tropical estuary during the dry season

AbstractEstuaries are usually characterized by strong spatial and temporal variability in water physicochemical conditions and are often largely affected by human activities. One important source of variability is caused by tides that can swiftly alter not only physicochemical conditions but also the abundance and composition of the biota. The effect of the diurnal tidal cycle on microbial community composition during different seasons remains uncertain, although this knowledge underlies having effective monitoring programs for water quality and potential identification of health risk conditions. In this study, we assessed the bacterioplankton community composition and diversity across four tidal water levels in a tropical estuary characterized by a mixed semidiurnal tide regime (i.e., two high and two low tides of varying amplitudes) during both dry and wet seasons. The bacterial community composition varied significantly among the four tidal levels, but only during the dry season, when the influence of the seawater intrusion was largest. Bacterial indicators’ taxa identified using the Indicator Value Index were found within Cyanobacteria, Actinobacteriota, Bacteroidota, and Proteobacteria. The indicator taxon Cyanobium sp. had a prominent presence across multiple tidal levels. The main predicted phenotypes of the bacterial communities were associated with potential pathogenicity, gram-negative, and biofilm formation traits. While there were no marked predicted phenotypic differences between seasons, pathogenic and gram-negative traits were more prevalent in the dry season, while biofilm formation traits dominated in the wet season. Overall, our findings underscore the intricate relationship between river hydrodynamics and bacterial composition variability and hint a significant human impact on the water quality of the Bangpakong River.

Characterizing virulence differences in a parasitoid wasp through comparative transcriptomic and proteomic

BackgroundTwo strains of the endoparasitoid Cotesia typhae (Hymenoptera: Braconidae) present a differential parasitism success on the host, Sesamia nonagrioides (Lepidoptera: Noctuidae). One is virulent on both permissive and resistant host populations, and the other only on the permissive host. This interaction provides a very interesting frame for studying virulence factors. Here, we used a combination of comparative transcriptomic and proteomic analyses to unravel the molecular basis underlying virulence differences between the strains.ResultsFirst, we report that virulence genes are mostly expressed during the pupal stage 24 h before adult emergence of the parasitoid. Especially, 55 proviral genes are up-regulated at this stage, while their expression is only expected in the host. Parasitoid gene expression in the host increases from 24 to 96 h post-parasitism, revealing the expression of 54 proviral genes at early parasitism stage and the active participation of teratocytes to the parasitism success at the late stage. Secondly, comparison between strains reveals differences in venom composition, with 12 proteins showing differential abundance. Proviral expression in the host displays a strong temporal variability, along with differential patterns between strains. Notably, a subset of proviral genes including protein-tyrosine phosphatases is specifically over-expressed in the resistant host parasitized by the less virulent strain, 24 h after parasitism. This result particularly hints at host modulation of proviral expression. Combining proteomic and transcriptomic data at various stages, we identified 8 candidate genes to support the difference in reproductive success of the two strains, one proviral and 7 venom genes, one of them being also produced within the host by the teratocytes.ConclusionsThis study sheds light on the temporal expression of virulence factors of Cotesia typhae, both in the host and in the parasitoid. It also identifies potential molecular candidates driving differences in parasitism success between two strains. Together, those findings provide a path for further exploration of virulence mechanisms in parasitoid wasps, and offer insights into host-parasitoid coevolution.

Early Pleistocene Orbital‐Scale Variability in Australian Northwest Shelf Sediments

AbstractPaleoclimate proxy records from regions sensitive to humidity/aridity extremes provide crucial insights into the natural forcing mechanisms underlying long‐term climate variability in broader regions. One such area is Northwest Australia, where the Australian monsoon impacts its northernmost fringes, which are bordered by the Great Sandy Desert inland. Marine sediments from the Australian Northwest Shelf record fluvial run‐off and eolian dust input during the wet and dry seasons, respectively. The location is therefore ideal for investigating long‐term variability in the Australian monsoon and Northwest Australian dust flux over orbital timescales. However, there are few continuous, high‐resolution paleoclimate records from this region spanning the early Pleistocene, when strong ice‐climate feedbacks of the late Pleistocene did not yet dominate global climate. Here, we present geochemical and environmental magnetic proxy records that reveal %CaCO3 and dust‐flux variability between 2.9 and 1.6 million years (Myr) ago from International Ocean Discovery Program Expedition 356 Site U1464 on the Australian Northwest Shelf. We establish a new, orbitally‐tuned chronology for Site U1464, primarily based on ∼400 thousand year (kyr) eccentricity cyclicity in %CaCO3, and observe strong obliquity variability (41 and 54 kyr periodicities) but almost no precession signal in the dust‐flux records. We propose that the 41 kyr cycle in Northwest Australian dust flux could be a linear response to East Asian winter monsoon intensity and/or the summer inter‐tropical insolation gradient (SITIG), whereas the 54 kyr cyclicity might be a non‐linear response to obliquity amplitude modulation via the SITIG effect on the cross‐equatorial atmospheric circulations.

Enhancing long-term vegetation monitoring in Australia: a new approach for harmonising the Advanced Very High Resolution Radiometer normalised-difference vegetation (NVDI) with MODIS NDVI

Abstract. Long-term, reliable datasets of satellite-based vegetation condition are essential for understanding terrestrial ecosystem responses to global environmental change, particularly in Australia, which is characterised by diverse ecosystems and strong interannual climate variability. We comprehensively evaluate several existing global Advanced Very High Resolution Radiometer (AVHRR) normalised-difference vegetation index (NDVI) products for their suitability for long-term vegetation monitoring in Australia. Comparisons with the MODIS NDVI highlight significant deficiencies, particularly over densely vegetated regions. Moreover, all the assessed products failed to adequately reproduce the interannual variability in the pre-MODIS era as indicated by Landsat NDVI anomalies. To address these limitations, we propose a new approach to calibrating and harmonising NOAA's Climate Data Record of AVHRR NDVI to the MODIS MCD43A4 NDVI for Australia using a gradient-boosting decision tree ensemble method. Two versions of the datasets are developed, one incorporating climate data in the predictors (“AusENDVI-clim”: Australian Empirical NDVI-climate) and another that is independent of climate data (“AusENDVI-noclim”). These datasets, spanning 1982–2013 at a spatial resolution of 0.05° and with a monthly time step, exhibit strong correlations (r2=0.89–0.94) and low mean errors compared with MODIS MCD43A4 NDVI (mean absolute error (MAE) = 0.014–0.028, RMSE = 0.021–0.046), accurately reproducing seasonal cycles over densely vegetated regions. Furthermore, they closely replicate the interannual variability in vegetation condition in the pre-MODIS era. A reliable method for gap-filling the AusENDVI record is also developed that leverages climate, atmospheric CO2 concentration, and woody-cover fraction predictors. The resulting synthetic NDVI dataset shows excellent agreement with the MODIS MCD43A4 NDVI and the recalibrated AVHRR NDVI time series (r2=0.82–0.95, MAE = 0.016–0.029, RMSE = 0.039–0.041). Finally, we provide a complete 41-year dataset where the gap-filled AusENDVI-clim from January 1982 to February 2000 is joined with the MODIS MCD43A4 NDVI from March 2000 to December 2022. Analysing 40-year per-pixel trends in Australia's annual maximum NDVI revealed increasing values, and shifts in the timing, of the annual peak NDVI across most of the continent, underscoring the dataset's potential to address crucial questions regarding the changing vegetation phenology and its drivers. The AusENDVI dataset can be used for studying Australia's changing vegetation dynamics and downstream impacts on the terrestrial carbon and water cycles, and it provides a reliable foundation for further research into the drivers of vegetation change. AusENDVI is open access and available at https://doi.org/10.5281/zenodo.10802703 (Burton et al., 2024).

Data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on multi-head attention mechanism

Accurate and reliable daily reservoir inflow forecast plays an essential role in several applications involving the management and planning of water resources, such as hydroelectric generation, flood control, water supply, and basin ecological dispatching. Runoff usually exhibits strong non-linearity, high uncertainty, and spatial and temporal variability. Existing techniques fail to capture complete dynamics change processes effectively. A data-driven forecasting framework for daily reservoir inflow time series considering the flood peaks based on a multi-head attention mechanism was developed, referred to as the GWOCS-VMD-CNN-Transformer (GCVCT). First, the model utilize Grey Wolf Optimizer coupled with Cuckoo Search (GWO-CS) algorithms to optimize parameters in variational mode decomposition model (VMD). This approach helps obtain highly correlated intrinsic mode function (IMF) components, enhancing the frequency resolution of the input dataset. The proposed method overcomes the bottleneck of other available methods by decomposing the time series to capture the main long-term and short-term properties of hydrological processes. Second, the convolution neural network and Transformer (CNN-Transformer) are based on a multi-head attention mechanism as the objective predictive method. Finally, six evaluation indicators verify the performance of the proposed approach. The approach’s reliability was evaluated using the historical daily reservoir inflow data from the Xiluodu (XLD) and Wudongde (WDD) reservoirs in the Jinsha River Basin, China. Several single and hybrid models were developed for comparative analysis. The results indicate that the proposed ensemble approach fits better than other developed model methods. The GCVCT model showed excellent performance in forecasting the inflows of XLD and WDD reservoirs, with NSE values of 0.985 and 0.984, respectively. Furthermore, the GCVCT framework forecast capacity for peak inflow was further verified through discussion and analysis of the 48 peak flows during the validation period, consistently outperforming other models in predicting peak flow for both study reservoirs. This framework provides an effective method for the scientific optimal scheduling of hydropower reservoirs, enabling more sustainable and efficient management practices. It also demonstrates the potential of powerful deep-learning models in intelligent hydrological forecasting.