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High pressure and high temperature experiments performed with laser-heated diamond anvil cells (LH-DAC) are being extensively used in geosciences to study matter at conditions prevailing in planetary interiors. Due to the size of the apparatus itself, the samples that are produced are extremely small, on the order of few tens of micrometers. There are several ways to analyze the samples and extract physical, chemical or structural information, using either in situ or ex situ methods. In this paper, we compare two nanoprobe techniques, namely nano-XRF and NanoSIMS, that can be used to analyze recovered samples synthetized in a LH-DAC. With these techniques, it is possible to extract the spatial distribution of chemical elements in the samples. We show the results for several standards and discuss the importance of proper calibration for the acquisition of quantifiable results. We used these two nanoprobe techniques to retrieve elemental ratios of dilute species (few tens of ppm) in quenched experimental molten samples relevant for the formation of the iron-rich core of the Earth. We finally discuss the applications of such probes to constrain the partitioning of trace elements between metal and silicate phases, with a focus on moderately siderophile elements, tungsten and molybdenum.
A 3-D crustal shear wave velocity model and Moho map below the Semail Ophiolite, eastern Arabia
(2022)
The Semail Ophiolite in eastern Arabia is the largest and best-exposed slice of oceanic lithosphere on land. Detailed knowledge of the tectonic evolution of the shallow crust, in particular during and after ophiolite obduction in Late Cretaceous times is contrasted by few constraints on physical and compositional properties of the middle and lower continental crust below the obducted units. The role of inherited, pre-obduction crustal architecture remains therefore unaccounted for in our understanding of crustal evolution and the present-day geology. Based on seismological data acquired during a 27-month campaign in northern Oman, Ambient Seismic Noise Tomography and Receiver Function analysis provide for the first time a 3-D radially anisotropic shear wave velocity (V-S) model and a consistent Moho map below the iconic Semail Ophiolite. The model highlights deep crustal boundaries that segment the eastern Arabian basement in two distinct units. The previously undescribed Western Jabal Akhdar Zone separates Arabian crust with typical continental properties and a thickness of similar to 40-45 km in the northwest from a compositionally different terrane in the southeast that is interpreted as a terrane accreted during the Pan-African orogeny in Neoproterozoic times. East of the Ibra Zone, another deep crustal boundary, crustal thickness decreases to 30-35 km and very high lower crustal V-S suggest large-scale mafic intrusions into, and possible underplating of the Arabian continental crust that occurred most likely during Permian breakup of Pangea. Mafic reworking is sharply bounded by the (upper crustal) Semail Gap Fault Zone, northwest of which no such high velocities are found in the crust. Topography of the Oman Mountains is supported by a mild crustal root and Moho depth below the highest topography, the Jabal Akhdar Dome, is similar to 42 km. Radial anisotropy is robustly resolved in the upper crust and aids in discriminating dipping allochthonous units from autochthonous sedimentary rocks that are indistinguishable by isotropic V-S alone. Lateral thickness variations of the ophiolite highlight the Haylayn Ophiolite Massif on the northern flank of Jabal Akhdar Dome and the Hawasina Window as the deepest reaching unit. Ophiolite thickness is similar to 10 km in the southern and northern massifs, and <= 5 km elsewhere.
The Kolumbo submarine volcano in the southern Aegean (Greece) is associated with repeated seismic unrest since at least two decades and the causes of this unrest are poorly understood. We present a ten-month long microseismicity data set for the period 2006-2007. The majority of earthquakes cluster in a cone-shaped portion of the crust below Kolumbo. The tip of this cone coincides with a low Vp-anomaly at 2-4 km depth, which is interpreted as a crustal melt reservoir. Our data set includes several earthquake swarms, of which we analyze the four with the highest events numbers in detail. Together the swarms form a zone of fracturing elongated in the SW-NE direction, parallel to major regional faults. All four swarms show a general upward migration of hypocenters and the cracking front propagates unusually fast, compared to swarms in other volcanic areas. We conclude that the swarm seismicity is most likely triggered by a combination of pore-pressure perturbations and the re-distribution of elastic stresses. Fluid pressure perturbations are induced likely by obstructions in the melt conduits in a rheologically strong layer between 6 and 9 km depth. We conclude that the zone of fractures below Kolumbo is exploited by melts ascending from the mantle and filling the crustal melt reservoir. Together with the recurring seismic unrest, our study suggests that a future eruption is probable and monitoring of the Kolumbo volcanic system is highly advisable.
Granitoids of the Slavkov Domain of the Brunovistulian microcontinent (BVM) in the Czech Republic have Ediacaran U-Pb zircon crystallization ages with the dominant magmatic activity occurring between ca. 597 and 595 Ma. The ages overlap published ages for the adjacent Thaya Domain, showing that both domains formed coevally in the same subduction setting. The data support published models in which the Slavkov Domain formed as arc crust. The main stage of magmatism stopped after ca. 595-590 Ma and was quickly followed by cooling accompanied by intrusion of small volumes of rhyolite dykes at ca. 594 Ma. Slavkov Domain metasedimentary rocks are dominated by Cryogenian-Ediacaran detrital zircon populations and their protoliths were locally derived erosional products of Cryogenian to Ediacaran arc rocks of the Thaya and Slavkov domains. Metasedi-mentary rocks from the NE part of the BVM contain younger, ca. 550 Ma zircons indicating that the BVM grew northeastward by accretion of progressively younger material derived from magmatic rocks with latest Ediacaran crystallization ages. In contrast to the Thaya and Slavkov domains, the Metavolcanic Zone that lies between them formed between ca. 740 and 725 Ma in the late Tonian to early Cryogenian. It predates the main stage magmatic activity in the BVM by 135 to 150 Ma and is probably a relic of older crust that formed during rifting of the Rodinia supercontinent. At ca. 552-551 Ma in the latest Ediacaran, parts of the BVM were exposed at the surface, during which time red, terrestrial siliciclastic sediments (Basal Clastics) were deposited. These largely had (very) proximal sources such as the main stage granitoids of the Thaya and Slavkov domains. Clasts of (meta)sandstones contain much older zircon populations and provide evidence that Neoarchaean and Palaeo-, meso- and early Neoproterozoic crustal rocks were exposed in erosional position nearby.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Through its magnetic activity, the Sun governs the conditions in Earth's vicinity, creating space weather events, which have drastic effects on our space- and ground-based technology.
One of the most important solar magnetic features creating the space weather is the solar wind that originates from the coronal holes (CHs).
The identification of the CHs on the Sun as one of the source regions of the solar wind is therefore crucial to achieve predictive capabilities.
In this study, we used an unsupervised machine-learning method, k-means, to pixel-wise cluster the passband images of the Sun taken by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory in 171, 193, and 211 angstrom in different combinations.
Our results show that the pixel-wise k-means clustering together with systematic pre- and postprocessing steps provides compatible results with those from complex methods, such as convolutional neural networks.
More importantly, our study shows that there is a need for a CH database where a consensus about the CH boundaries is reached by observers independently.
This database then can be used as the "ground truth," when using a supervised method or just to evaluate the goodness of the models.
Modern pollen-vegetation-climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen-vegetation-climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.
As the recent permafrost thawing of northern Asia proceeds due to anthropogenic climate change, precise and detailed palaeoecological records from past warm periods are essential to anticipate the extent of future permafrost variations. Here, based on the modern relationship between permafrost and vegetation (represented by pollen assemblages), we trained a Random Forest model using pollen and permafrost data and verified its reliability to reconstruct the history of permafrost in northern Asia during the Holocene. An early Holocene (12-8 cal ka BP) strong thawing trend, a middle-to-late Holocene (8-2 cal ka BP) relatively slow thawing trend, and a late Holocene freezing trend of permafrost in northern Asia are consistent with climatic proxies such as summer solar radiation and Northern Hemisphere temperature. The extensive distribution of permafrost in northern Asia inhibited the spread of evergreen coniferous trees during the early Holocene warming and might have decelerated the enhancement of the East Asian summer monsoon (EASM) by altering hydrological processes and albedo. Based on these findings, we suggest that studies of the EASM should consider more the state of permafrost and vegetation in northern Asia, which are often overlooked and may have a profound impact on climate change in this region.
Although phytoliths are recognized as an important proxy for paleoenvironmental reconstruction, the quantitative relationship between phytoliths and climate is still debated. In order to provide an improved basis for phytolith-based paleoclimate reconstructions, a representative modern phytolith dataset is essential. Here, we synthesize a modern topsoil phytolith dataset for Northeast China, analyze its climatic significance, and apply it to a fossil phytolith series from the Hani peat core in Northeast China. The dataset comprises 660 topsoil phytolith assemblages from 289 sample sites. We compiled modern meteorological data to assess the quantitative relationship between the phytolith assemblages and climatic variables. Detrended correspondence analysis (DCA) and Redundancy analysis (RDA) were used to determine the dominant climatic variable influencing the phytolith distributions. The results showed that mean annual temperature (MAT) is the dominant variable controlling the spatial distribution of phytoliths, accounting for 8.91% of the total variance. Transfer function based on inverse deshrinking locally-weighted weighted averaging (LWWA_Inv) was developed for MAT (R-_boot(2) = 0.86, RMSEP = 1.02 degrees C). Applying the LWWA_Inv transfer function to fossil phytolith records from the Hani peat core enables quantitative inferences to be made about Holocene climate changes in Northeast China. Overall, combined with the LWWA_Inv method, the topsoil phytolith dataset of Northeast China can be used for reliable quantitative MAT reconstruction.
We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
Fast Holocene slip and localized strain along the Liquiñe-Ofqui strike-slip fault system, Chile
(2021)
In active tectonic settings dominated by strike-slip kinematics, slip partitioning across subparallel faults is a common feature; therefore, assessing the degree of partitioning and strain localization is paramount for seismic hazard assessments. Here, we estimate a slip rate of 18.8 +/- 2.0 mm/year over the past 9.0 +/- 0.1 ka for a single strand of the Liquirie-Ofqui Fault System, which straddles the Main Cordillera in Southern Chile. This Holocene rate accounts for similar to 82% of the trench-parallel component of oblique plate convergence and is similar to million-year estimates integrated over the entire fault system. Our results imply that strain localizes on a single fault at millennial time scale but over longer time scales strain localization is not sustained. The fast millennial slip rate in the absence of historical Mw> 6.5 earthquakes along the Liquine-Ofqui Fault System implies either a component of aseismic slip or Mw similar to 7 earthquakes involving multi-trace ruptures and > 150-year repeat times. Our results have implications for the understanding of strike-slip fault system dynamics within volcanic arcs and seismic hazard assessments.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Rupture directivity, implying a predominant earthquake rupture propagation direction, is typically inferred upon the identification of 2D azimuthal patterns of seismic observations for weak to large earthquakes using surface-monitoring networks. However, the recent increase of 3D monitoring networks deployed in the shallow subsurface and underground laboratories toward the monitoring of microseismicity allows to extend the directivity analysis to 3D modeling, beyond the usual range of magnitudes. The high-quality full waveforms recorded for the largest, decimeter-scale acoustic emission (AE) events during a meter-scale hydraulic fracturing experiment in granites at similar to 410 m depth allow us to resolve the apparent durations observed at each AE sensor to analyze 3D-directivity effects. Unilateral and (asymmetric) bilateral ruptures are then characterized by the introduction of a parameter kappa, representing the angle between the directivity vector and the station vector. While the cloud of AE activity indicates the planes of the hydrofractures, the resolved directivity vectors show off-plane orientations, indicating that rupture planes of microfractures on a scale of centimeters have different geometries. Our results reveal a general alignment of the rupture directivity with the orientation of the minimum horizontal stress, implying that not only the slip direction but also the fracture growth produced by the fluid injections is controlled by the local stress conditions.
Dispersion-curve inversion of Rayleigh waves to infer subsurface shear-wave velocity is a long-standing problem in seismology. Due to nonlinearity and ill-posedness, sophisticated regularization techniques are required to solve the problem for a stable velocity model. We have formulated the problem as a minimization problem with nonlinear operator constraint and then solve it by using an inexact augmented Lagrangian method, taking advantage of the Haney-Tsai Dix-type relation (a global linear approximation of the nonlinear forward operator). This replaces the original regularized nonlinear problem with iterative minimization of a more tractable regularized linear problem followed by a nonlinear update of the phase velocity (data) in which the update can be performed accurately with any forward modeling engine, for example, the finite-element method. The algorithm allows discretizing the medium with thin layers (for the finite-element method) and thus omitting the layer thicknesses from the unknowns and also allows incorporating arbitrary regularizations to shape the desired velocity model. In this research, we use total variation regularization to retrieve the shear-wave velocity model. We use two synthetic and two real data examples to illustrate the performance of the inversion algorithm with total variation regularization. We find that the method is fast and stable, and it converges to the solution of the original nonlinear problem.
Lithium and boron are trace components of magmas, released during exsolution of a gas phase during volcanic activity.
In this study, we determine the diffusivity and isotopic fractionation of Li and B in hydrous silicate melts.
Two glasses were synthesized with the same rhyolitic composition (4.2 wt% water), having different Li and B contents; these were studied in diffusion-couple experiments that were performed using an internally heated pressure vessel, operated at 300 MPa in the temperature range 700-1250 degrees C for durations from 0 s to 24 h. From this we determined activation energies for Li and B diffusion of 57 +/- 4 kJ/mol and 152 +/- 15 kJ/mol with pre-exponential factors of 1.53 x 10(-7) m(2)/s and 3.80 x 10(-8) m(2)/s, respectively.
Lithium isotopic fractionation during diffusion gave beta values between 0.15 and 0.20, whereas B showed no clear isotopic fractionation.
Our Li diffusivities and isotopic fractionation results differ somewhat from earlier published values, but overall confirm that Li diffusivity increases with water content. Our results on B diffusion show that similarly to Li, B mobility increases in the presence of water.
By applying the Eyring relation, we confirm that B diffusivity is limited by viscous flow in silicate melts.
Our results on Li and B diffusion present a new tool for understanding degassing-related processes, offering a potential geospeedometer to measure volcanic ascent rates.
Ground-motion models (GMMs) are often used to predict the random distribution of Spectral accelerations (SAs) at a site due to a nearby earthquake. In probabilistic seismic hazard and risk assessment, large earthquakes occurring close to a site are considered as critical scenarios. GMMs are expected to predict realistic SAs with low within-model uncertainty (sigma(mu)) for such rare scenarios. However, the datasets used to regress GMMs are usually deficient of data from critical scenarios. The (Kotha et al., A Regionally Adaptable Ground-Motion Model for Shallow Crustal Earthquakes in Europe Bulletin of Earthquake Engineering 18:4091-4125, 2020) GMM developed from the Engineering strong motion (ESM) dataset was found to predict decreasing short-period SAs with increasing M-W >= M-h = 6.2, and with large sigma(mu) at near-source distances <= 30km. In this study, we updated the parametrisation of the GMM based on analyses of ESM and the Near source strong motion (NESS) datasets. With M-h = 5.7, we could rectify the M-W scaling issue, while also reducing sigma(mu). at M-W >= M-h. We then evaluated the GMM against NESS data, and found that the SAs from a few large, thrust-faulting events in California, New Zealand, Japan, and Mexico are significantly higher than GMM median predictions. However, recordings from these events were mostly made on soft-soil geology, and contain anisotropic pulse-like effects. A more thorough non-ergodic treatment of NESS was not possible because most sites sampled unique events in very diverse tectonic environments. We provide an updated set of GMM coefficients,sigma(mu), and heteroscedastic variance models; while also cautioning against its application for M-W <= 4 in low-moderate seismicity regions without evaluating the homogeneity of M-W estimates between pan-European ESM and regional datasets.
Today, near-surface investigations are frequently conducted using non-destructive or minimally invasive methods of applied geophysics, particularly in the fields of civil engineering, archaeology, geology, and hydrology. One field that plays an increasingly central role in research and engineering is the examination of sedimentary environments, for example, for characterizing near-surface groundwater systems. A commonly employed method in this context is ground-penetrating radar (GPR). In this technique, short electromagnetic pulses are emitted into the subsurface by an antenna, which are then reflected, refracted, or scattered at contrasts in electromagnetic properties (such as the water table). A receiving antenna records these signals in terms of their amplitudes and travel times. Analysis of the recorded signals allows for inferences about the subsurface, such as the depth of the groundwater table or the composition and characteristics of near-surface sediment layers. Due to the high resolution of the GPR method and continuous technological advancements, GPR data acquisition is increasingly performed in three-dimensional (3D) fashion today.
Despite the considerable temporal and technical efforts involved in data acquisition and processing, the resulting 3D data sets (providing high-resolution images of the subsurface) are typically interpreted manually. This is generally an extremely time-consuming analysis step. Therefore, representative 2D sections highlighting distinctive reflection structures are often selected from the 3D data set. Regions showing similar structures are then grouped into so-called radar facies. The results obtained from 2D sections are considered representative of the entire investigated area. Interpretations conducted in this manner are often incomplete and highly dependent on the expertise of the interpreters, making them generally non-reproducible.
A promising alternative or complement to manual interpretation is the use of GPR attributes. Instead of using the recorded data directly, derived quantities characterizing distinctive reflection structures in 3D are applied for interpretation. Using various field and synthetic data sets, this thesis investigates which attributes are particularly suitable for this purpose. Additionally, the study demonstrates how selected attributes can be utilized through specific processing and classification methods to create 3D facies models. The ability to generate attribute-based 3D GPR facies models allows for partially automated and more efficient interpretations in the future. Furthermore, the results obtained in this manner describe the subsurface in a reproducible and more comprehensive manner than what has typically been achievable through manual interpretation methods.
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Effect of temperature on the densification of silicate melts to lower earth's mantle conditions
(2022)
Physical properties of silicate melts play a key role for global planetary dynamics, controlling for example volcanic eruption styles, mantle convection and elemental cycling in the deep Earth. They are significantly modified by structural changes at the atomic scale due to external parameters such as pressure and temperature or due to chemistry. Structural rearrangements such as 4- to 6-fold coordination change of Si with increasing depth may profoundly influence melt properties, but have so far mostly been studied at ambient temperature due to experimental difficulties. In order to investigate the structural properties of silicate melts and their densification mechanisms at conditions relevant to the deep Earth's interior, we studied haplo basaltic glasses and melts (albite-diopside composition) at high pressure and temperature conditions in resistively and laser-heated diamond anvil cells using X-ray absorption near edge structure spectroscopy. Samples were doped with 10 wt% of Ge, which is accessible with this experimental technique and which commonly serves as a structural analogue for the network forming cation Si. We acquired spectra on the Ge K edge up to 48 GPa and 5000 K and derived the average Ge-O coordination number NGe-O, and bond distance RGe-O as functions of pressure. Our results demonstrate a continuous transformation from tetrahedral to octahedral coordination between ca. 5 and 30 GPa at ambient temperature. Above 1600 K the data reveal a reduction of the pressure needed to complete conversion to octahedral coordination by ca. 30 %. The results allow us to determine the influence of temperature on the Si coordination number changes in natural melts in the Earth's interior. We propose that the complete transition to octahedral coordination in basaltic melts is reached at about 40 GPa, corresponding to a depth of ca. 1200 km in the uppermost lower mantle. At the core-mantle boundary (2900 km, 130 GPa, 3000 K) the existence of non-buoyant melts has been proposed to explain observed low seismic wave velocity features. Our results highlight that the melt composition can affect the melt density at such extreme conditions and may strongly influence the structural response.