Evidence for terrane boundaries and suture zones across Southern Mongolia detected with a 2-dimensional magnetotelluric transect
KeywordsMagnetotellurics Electrical resistivity Southern Mongolia Gobi Terranes Suture zones
Central Asian Orogenic Belt
root mean square
Terranes are defined as fault-bounded fragments whose surface geology differs from that of adjacent areas (e.g., Badarch et al. 2002; Kröner et al. 2010). However, attempts to match lithostratigraphic domains to surface faulting (using geochronology, structural constraints, and aerial potential field measurements) have revealed some disagreements in the positions of suspected terranes (e.g., Badarch et al. 2002; Kröner et al. 2010; Guy et al. 2014). Geophysical potential field data (gravity and magnetics) are useful to distinguish lithostratigraphic domains because gravity and magnetic signals depend on the specific petrophysical properties of the rock components (that is, density and magnetic susceptibility). However, the main challenge with potential field data is to accurately interpret the depth of each feature. In fact, potential field data have shown close agreement with the four principal tectonic zones (Guy et al. 2014). Unfortunately, this region lacks seismic data, which could provide new evidence for lithospheric structure.
Instead of identifying terranes by the distinguishable variations in crustal properties between them, due to their unique petrophysical properties and rock types, they can instead be identified by their boundaries, which are rheological weak zones between them. As mentioned above, if the contrasting lithostratigraphic domains represent distinct terranes they should be partitioned and bounded by faults and suture zones that are suspected to be crustal or lithospheric-scale (e.g., Badarch et al. 2002; Calais et al. 2003). However, due to the extended intracontinental convergent deformation in this region, these faults and suture zones may be very narrow zones, or covered at the surface, and thus difficult to detect (e.g., Dewey 1977). Hence geophysical methods that can accurately image deep crustal structures are required.
Magnetotelluric (MT) data image subsurface electrical resistivity using natural electromagnetic signals measured over a broad range of frequencies (e.g., Chave and Jones 2012). The resistivity of a rock is a unique geophysical signature, which can vary over several orders of magnitude, and is especially sensitive to the quantity and composition of crustal fluids and partial melt. Because faults and suture zones are regions of fractured, weakened crust, due to past and present deformation, they often have circulating fluids that act to decrease their electrical resistivity (e.g., Türkoğlu et al. 2008; Unsworth and Rondenay 2012). Hence the MT method is useful for investigating subsurface fault distributions, and therefore has the potential to identify tectonic zones by imaging their boundaries.
Here, we present high-resolution MT measurements across Southern Mongolia. Electrical resistivity models of the lithosphere, in combination with previous geological and geophysical data, provide insights into both the shallow surface and deep structure of this region and help to shed light on the distribution of tectonic blocks and the development of the CAOB.
Data acquisition and analysis
Magnetotelluric data consist of electric and magnetic fields measured at the surface of the Earth that are related by a frequency-dependent, complex-valued impedance tensor (Z) that is sensitive to the Earth’s subsurface electrical resistivity structure (e.g., Chave and Jones 2012). Apparent resistivity (and impedance phase) are determined over a range of frequencies, with high frequencies sensitive to shallow structure and low frequencies (i.e., long periods) sampling greater depths.
Beginning in 2016, an array of MT data was collected across Central Mongolia in order to investigate the subsurface electrical resistivity, specifically below the Hangai Dome (Käufl et al. 2020; Comeau et al. 2018a). In 2018, a profile of 20 MT sites was completed in Southern Mongolia, along a longitude of approximately 100.5° E and ending near the China–Mongolia border (~ 20 km away). Combining these with previously acquired data, a profile was created (total range: latitude 45.950° N to 42.897° N) that will be the focus of this paper (see Fig. 1).
Both MT instruments and telluric-only data-loggers were deployed. Telluric-only data-loggers were developed and built by the University of Münster (Becken et al. 2014), and used non-polarizing Pb–PbCl2 electrodes, based on the design of Petiau (2000), which are stable for long periods. MT instruments consisted of a combination of Metronix ADU-07e data-loggers (deployed in 2018; provided by the Geothermal Energy and Geofluids group at ETH Zurich, and by the University of Münster) and SPAM Mk IV data-loggers (deployed in 2016 and 2017, see Fig. 1; provided by the Geophysical Instrument Pool Potsdam, with Ag–AgCl electrodes). Metronix MFS-06e magnetic induction coils were used to measure the two horizontal magnetic field components. The vertical magnetic field was also measured at most MT sites, but is not used in this study. The electric dipole length was typically chosen to be 60 m. All instruments were powered with batteries and solar panels (< 100 W).
The total period range recorded was 0.00195–5793 s (half of the sites reached more than 1024 s), providing good resolution within the crust and allowing penetration to upper mantle depths. MT site occupation times were typically less than 3 days. All measurement sites had an average spacing of 8.5 km (range of 4–15 km), and MT measurements were carried out with an average spacing of 31 km (range of 5–50 km). This survey design ensured fast and efficient field deployment. Typically, there were two MT sites and a few telluric-only sites recording simultaneously. Inter-site transfer functions were computed between the telluric-only sites and the full MT sites, using a combination of local electric fields and magnetic fields from the base site, as described by Käufl et al. (2020). Some modelling codes are capable of accounting for the independent measurement locations of the electric fields and the magnetic fields (e.g., Key 2016; Grayver 2015; Kalscheuer et al. 2010). This is an improvement over simply using nearby magnetic fields for the telluric-only sites because this approach can introduce some error, specifically near strong resistivity contrasts (e.g., Muñoz and Ritter 2013), especially because the distances between local and base sites in this study are large (cf. Comeau 2015).
Phase tensor analysis was used to verify this result. The phase tensors (Fig. 3), which are not affected by galvanic distortions such as static shifts, can be plotted in pseudo-section view as ellipses and coloured with their phase tensor skew value (ψ; Booker 2014). They will appear as circles for a 1-D subsurface and as ellipses for 2-D or 3-D subsurface conductivity distributions. Skew values for perfect 2-D data are 0°, whereas high skew values (> 6°) indicate significant 3-D effects (e.g., Booker 2014). It was found that average skew values across the profile were low (skew < 3°, ~ 70% of data). Hence, the phase tensor analysis confirmed that a 2-D model is valid, although certain regions displayed distortion or local 3-D resistivity structures. To account for this, data with high phase tensor skew values (e.g., > 9°) can be omitted. For modelling purposes, the data were mathematically rotated to the geo-electric strike direction (N104° E) and projected along a profile perpendicular to this, following the assumption that the subsurface resistivity does not vary away from the profile (i.e., it is 2-D).
In order to properly account for the effects of galvanic distortion and departures from the 2-D condition, the distortion parameterization of Becken and Burkhardt (2004) was employed. This parameterization yields the distortion angles introduced by Smith (1995) if the 2-D condition is fulfilled. In this case, distortion can be partly removed by constructing an inverse distortion matrix. Otherwise, the telluric vectors exhibit an elliptical polarization state, an admission of departures from true 2-D conditions, or of a non-optimal principal axis (corresponding to the chosen geo-electric strike direction). However, all data have errors and any 2-D condition can only be confirmed to within the errors of the ellipticities. Non-vanishing ellipticities can be back-propagated into impedance errors, as in Becken et al. (2011). Thus these new impedance errors make departures from the 2-D condition indistinguishable, within the errors. This procedure of adjusting the errors corresponds to the down-weighting of 3-D effects (i.e., using the errors in the inversion as weightings).
2-Dimensional data modelling
The profile contained 39 MT sites and included data at 39 periods, in the range of 0.00781–4096 s. Both modes of the impedance tensor were inverted (i.e., the transverse magnetic or TM mode with electric currents flowing along the profile and the perpendicular transverse electric or TE mode). Käufl et al. (2018) investigated the effect of topography when modelling MT data, and showed that the distortion of MT data can occur when it is not accounted for. Topography was included in the model, because the elevation in this region varies from 700 to 3957 m above sea level (crossing Ih Bogdin in the Gobi–Altai mountains). The starting model consisted of homogenous 300 Ωm halfspace, which corresponds to the mean value for the entire region, as determined by the previous analysis (see Fig. 2).
In order to keep the model resolution high and to fit a broad period range, the modelling mesh used seven layers, with the dimensions of the mesh elements increasing downwards (see Fig. 4). Between the surface and sea level, a fine mesh of triangular elements had dimensions of approximately 0.5 km. Below this, from sea-level to 2 km depth below sea-level, the elements had dimensions of 1 km; from 2 to 10 km depth, dimensions of 2 km; from 10 to 45 km depth (the bottom of the crust), dimensions of 3 km; from 45 to 90 km depth, dimensions of 5 km; from 90 to 200 km depth, dimensions of 10 km; and finally from 200 to 1000 km depth the elements expanded smoothly to a maximum dimension of 150 km. In total, the modelling mesh had 31,701 triangular elements.
Many combinations of inversion model parameters and inversion approaches were thoroughly investigated in order to test the robustness of model features. Overall, it was found that the main resistivity features of the model did not heavily depend on any specific scheme and the preferred model shown here is representative of most cases. For example, no significant changes in the main model features were observed when the geo-electric strike angle was varied slightly (i.e., ± 10°), or when the starting model was reasonably varied (e.g., to a layered starting model, or to a 100 Ωm halfspace). Only relatively minor changes in the data fit or time of convergence were seen. Additionally, the inversion was carried out using only data with low phase tensor skew (ψ < 6°) to better match the assumptions of 2-D modelling and eliminate any off-profile effects due to 3-D structure. Similarly, we removed short period data (< 1 s), representative of the near-surface structure (< 5 km) which were generally more difficult to fit. In both cases the data fit improved, but the main model features did not undergo any relatively significant changes, despite a reduction in model resolution. Furthermore, model resolution and sensitivity were investigated systematically using synthetic inversions. This included removing model features (i.e., replacing a conductor with its adjacent resistivity values) and observing the change in data fit and re-inverting to investigate if features were re-introduced. These tests demonstrated that the main features are robust and required. Crustal features of the model are particularly well-constrained. However, the geometry of the upper mantle features is not well-constrained, and can vary. None of the variations observed affect the overall interpretation of the preferred model.
Results and discussion
The 2-D resistivity model derived from the MT data reveals several interesting features, described and discussed below. Variations in resistivity can be due to multiple causes (including different rock types, the presence of fluids, or partial melts), and therefore any interpretation of model features benefits from additional information (e.g., Unsworth and Rondenay 2012).
The near-surface layer (< 1.5 km) has a highly variable resistivity (3–3000 Ωm; see Fig. 4). It features two highly conductive regions (< 30 Ωm), in the Valley of Lakes (near Bogd), which is an internally drained basin between the Hangai and Gobi–Altai mountains (e.g., Cunningham 2001), and north of the Nemegtiyn mountain range (near Gurvantes), which is a Cenozoic alluvial basin (Badarch et al. 2002) (see Fig. 1 for locations). These conductive features may be caused by porous sediments in these regions or by increased salinity due to evaporite minerals. Another shallow (< 5 km) conductive feature (~ 100 Ωm; G1) is seen at the northern end of the profile. It is located below the Tsagaan Tsahir Uul gold deposit, which is an area of significant mineralization, containing important sources of gold and copper (e.g., Buchan et al. 2001; Dejidmaa and Badarch 1999). The observed electrical signature may be associated with emplaced mineralization in the upper crust, or past hydrothermal fluid alteration (see Comeau et al. 2018b).
The upper crust (< 20 km) is generally resistive (1000–30,000 Ωm). This can be explained by the Neoproterozoic basement rocks and Paleozoic ultra-mafic rocks believed to comprise this region (e.g., Guy et al. 2015; Badarch et al. 2002). Within the upper crust, MT data detect two prominent anomalously conductive features (30–100 Ωm; F1 and F2), imaged as elongated structures stretching nearly vertically through the upper crust to depths of 20+ km and dipping slightly southwards. The feature F1 was previously imaged by Comeau et al. (2018a) and has a consistent geometry and resistivity, despite differences in data preparation and inversion methodology. Both features F1 and F2 are well resolved by the dense MT site spacing. Faults and suture zones are regions of fractured and weakened crust that may contain circulating fluids or hydrothermally altered zones that significantly lower the electrical resistivity (e.g., Unsworth and Rondenay 2012). Therefore, these features are interpreted to represent suture zones.
In fact, these anomalous features are spatially associated with the surface expressions of known fault zones and inferred terrane boundaries (Badarch et al. 2002), which are expected to be deep-reaching, possibly lithospheric-scale (Calais et al. 2003). The feature F1 is coincident with the location of the large, seismically active, left-lateral strike–slip and transpressional Bogd fault zone at the base of Ih Bogdin and the Gobi–Altai mountain range (Walker et al. 2007; Calais et al. 2003). Moreover, it is known to be a major lithological boundary (Badarch et al. 2002), and is thought to be an ancient suture zone (e.g., Xiao et al. 2015). The epicentre of a large rupture event in 1957, which had a strike–slip mechanism and a moment magnitude larger than 8, is located less than 100 km to the west, near the Bayantsagaani mountain range (e.g., Calais et al. 2003, and references therein; Rizza et al. 2015). Furthermore, the locations of recently measured earthquakes (see Meltzer et al. 2019) align on each side of the feature F1, at depths of 0–17 km. The feature F2 is coincident with the major Gobi–Tienshan fault as it passes near the Nemegtiyn mountain range, which is a left-lateral strike–slip fault that stretches westward into China and can be continuously traced for more than 1000 km (e.g., Styron 2018; Walker et al. 2007).
Both features appear to dip southwards, approximately 70–80° to the horizontal. This is consistent with geological estimates of fault dips in this region (e.g., Rizza et al. 2015). Furthermore, these fault zones each consist of two surface traces with a broad zone between. Because a combination of strike–slip and transpressional faulting (along restraining bends) is observed here, we speculate that this may indicate a subsurface flower-structure, with the fault segments joining into a single strand in the basement. The fault extent at greater depths is speculative, but because these faults represent terrane sutures they are believed to be lithospheric-scale (e.g., Calais et al. 2003), that is, they are expected to pass through the crust into the upper mantle.
There is no near-surface conductive feature spatially aligned with the small Trans-Altai fault, located at the southern edge of the Gobi–Altai plateau and the Gichgeniy mountain range (e.g., Walker et al. 2007; Guy et al. 2014). However, a strong electrical signature is likely absent because deformation along this fault is primarily located to the west, where there is a step in surface topography, as indicated by the end of the mapped surface trace ~ 20 km west of the profile (see Fig. 1; Walker et al. 2007). Although tectonostratigraphic maps show this boundary extends farther east (Kröner et al. 2010). Additionally, this fault has very little seismic activity, historic or current (e.g., Meltzer et al. 2019). However, a deeper (mid-crustal) conductive anomaly (50–100 Ωm; C2) may be related to this fault system (see below). Similarly, no conductive feature is seen further south near the Toson Bumbin mountain range.
In contrast to the upper crust, the lower crust (20–45 km) has a generally moderate resistivity (300–1000 Ωm). Two lower-resistivity zones (50–100 Ωm) are observed beneath the Gobi–Altai zone (C1; 30–50 km depth, it appears smeared downwards) and the Trans-Altai zone (C2; 15–30 km depth). The low-resistivity zones are disconnected and offset, signifying a crustal boundary. According to global models for Curie-point depths (Li et al. 2017), the 550 °C temperature isotherm is at a depth of approximately 20 km in this region, indicating that feature C1 is located below the brittle–ductile transition and feature C2 is near it. The low-resistivity zones suggest that the crustal (lithotectonic) blocks are not homogenous. This may therefore agree with previous studies which have argued that an enigmatic and allochthonous lower crust exists below the Gobi–Altai zone and Trans-Altai zone (Guy et al. 2015; Kröner et al. 2010). One study, based on geochemical constraints and gravity modelling, concluded that the lower crust of the Mongolian CAOB in this region is felsic and juvenile metamorphosed continental crust due to the relamination of the Khantaishir magmatic arc (Guy et al. 2015). Therefore, these low-resistivity zones may be controlled by past deformation episodes. Alternatively, the anomaly C2 may be related to an ancient accretionary wedge associated with the Trans-Altai fault (Badarch et al. 2002; Guy et al. 2015) due to a previous subduction event north of the South-Gobi zone (e.g., Xiao et al. 2015). In contrast, the South-Gobi zone appears to have a homogenous lower crust (> 1000 Ωm), which is consistent with the fact that it is believed to consist of a Precambrian cratonic basement (Guy et al. 2014).
Although resolution at greater depths is limited, the resistivity model images several interesting features within the upper mantle. Below the northern portion of the profile, a conductive feature (~ 100 Ωm; M1) appears below a depth of 70 km. This is believed to be a continuation of the shallow asthenosphere previously detected below Central Mongolia (~ 70 km; Comeau et al. 2018a), which agreed with the architecture of the lithosphere–asthenosphere boundary predicted from a seismic profile across central Mongolia (Petit et al. 2008). For the southern portion of the profile (south of the Gobi–Altai Mountains), the MT data indicate a resistive upper mantle (~ 1000 Ωm). This gives evidence for a thick lithosphere (> 100 km) below Southern Mongolia. Hence, this indicates the presence of a steep lithospheric step. This is corroborated by modern global tomography models (Ho et al. 2016) that predict an increase of ~ 36 km in the thickness of the (thermal) lithosphere across the entire profile (from latitude 45° N to 43° N). In this study, the location of the lithospheric step is clearly imaged beneath the Gobi–Altai mountains, which can possibly be explained by the major suture zone running along the Main Mongolian Lineament (e.g., Xiao et al. 2015). Other studies (Comeau et al. 2018a; Petit et al. 2008) placed the step farther north, and related it to the major suture zone formed by the closure of the Mongol-Okhotsk ocean (e.g., Van der Voo et al. 2015; Sheldrick et al. 2018). In addition, an anomalous feature is imaged in the upper mantle below the South-Gobi zone (M2; 200–300 Ωm). It is unexplained, but may be related to the lithospheric-scale suture of the South-Gobi zone along the Gobi–Tienshan fault. Alternatively, it could be related to hydrated lithosphere, thought to exist in this region from previous subduction events, or it could be a consequence of a very local shallowing asthenosphere (e.g., Sheldrick et al. 2018).
Constraints on tectonic boundaries
Combining geological, geochemical, and geochronological data, Badarch et al. (2002) composed a model of Mongolia consisting of 44 separate lithostratigraphic domains interpreted as terranes. In Southern Mongolia, to first-order, narrow, east–west oriented terranes were amalgamated and accreted about a central nucleus (Badarch et al. 2002), which was separated by a major suture known as the Main Mongolian Lineament (e.g., Kröner et al. 2010; Xiao et al. 2015). This nucleus consisted of the cratonic block of Central Mongolia (Hangai) and microcontinent fragments, including the Baydrag block. Although terrane accretion was spatially and temporally complex, it is believed to have generally occurred north to south with time (e.g., Badarch et al. 2002). Terranes are expected to be fault-bounded fragments, but the lithostratigraphic domains do not consistently align with the position of known surface faults. Kröner et al. (2010), revisiting older models, simplified Southern Mongolia into four principal tectonic zones, or lithotectonic blocks (see Fig. 1). Geophysical potential field data analysed by Guy et al. (2014; gravity and magnetics) revealed minor disagreements in the positions of several suspected terranes, but supported the principal tectonic zones.
The Baydrag block is an early Proterozoic continental fragment overlain by a Cambrian passive margin (Guy et al. 2014; Kröner et al. 2010; Badarch et al. 2002). It is located in the Valley of Lakes, south of the Hangai, and separated by the South Hangai fault zone, and north of the Gobi–Altai (e.g., Badarch et al. 2002). the lake zone is a narrow tectonic zone adjacent to the Bogd fault system, and the Main Mongolian Lineament, that reaches from Baga Bogdin and Ih Bogdin mountain ranges to the Har Argalantin and Bayantsagaani mountain ranges and farther west (Kröner et al. 2010). Guy et al. (2015) describe it as an Early Cambrian accretionary wedge composed of volcanic arcs (possibly island arcs) and accretionary prisms thrust over the basement rocks of the Baydrag block. South of the Gobi–Altai mountains is a plateau, which defines the Gobi–Altai zone, which ends at the Trans-Altai fault. The Gobi–Altai zone consists of thick Cambrian/Ordovician volcano-sedimentary sequences interpreted as an accretionary wedge covered by Silurian/Devonian passive margin and high-grade metamorphic rocks (e.g., Guy et al. 2015). The Trans-Altai zone lies to the south and ends at the Gobi–Tienshan fault. This zone consists of Devonian marine sediments and volcanic rocks, representing a passive margin and a volcanic arc, as well as deeper ultra-mafic rocks that give evidence for the formation of oceanic crust during the Early Devonian, which corresponds with an ocean opening (e.g., Guy et al. 2015). South of this is the South-Gobi zone, which continues to the Mongolia–China border and beyond to another major suture zone in Northern China (Kröner et al. 2010; Xiao et al. 2015). This zone consists of Ordovician/Silurian siliciclastic sediments, typical of continental-margins, and Carboniferous volcanic rocks atop a Precambrian cratonic basement (Guy et al. 2014). In addition, both the Trans-Altai zone and the South-Gobi zone have intrusive Carboniferous and Permian granitoids, found to be related to basement melting from zircon analysis and located along the main tectonic boundaries, coinciding with weakened deformation zones (Guy et al. 2015).
Tectonic zones and terranes, in the classic sense, are fragments and must be bounded by suture zones, which are often deep-reaching. Therefore, by identifying suture zones, the terrane boundaries, we can identify individual terranes. However, ancient suture zones, especially those that have undergone convergent deformation, as is the case in Southern Mongolia, may be obscured and difficult to detect on the surface (e.g., Dewey 1977). Fortunately, faults and suture zones generally contain fluids, giving them an anomalous electrical signature compared to their surroundings, and allowing us to image them (Türkoğlu et al. 2008; Unsworth and Rondenay 2012).
As discussed above, the resistivity model clearly images several major fault zones. Therefore, the model agrees with the simplification of Kröner et al. (2010) for four principal tectonic zones (see Fig. 4). Nevertheless, distinct lithologies may exist within each tectonic zone, although their resistivity differences, due to differences in petrophysical properties and rock types, are not readily distinguishable, but we can conclude that they are not fault bounded. The distinct lithostratigraphic domains of Badarch et al. (2002) can be adjusted slightly so that they fit within the tectonic zones or along the suture zones. It should be noted that, from the resistivity model, we separate the tectonic regions based on the bounding faults only, rather than on other geological, geochronological, or structural constraints, which may cause small discrepancies with the inferred boundaries drawn by others.
In this study, MT and telluric-only data were collected along a ~ 350-km-long profile crossing Southern Mongolia, part of the CAOB, from the Hangai Mountains, across the Gobi–Altai Mountains, to the China–Mongolia border. The data were used to generate a high-resolution, 2-D electrical resistivity model of the crust and upper mantle, presented here. The electrical resistivity model offers new insights into the structure of Southern Mongolia, which plays an important role in understanding the origin and evolution of the CAOB.
Various attempts have been made to divide Southern Mongolia into distinct lithostratigraphic or tectonic regions, typically attributed to accreted terranes. However, there has been some controversy about the exact locations and boundaries of these regions. Terranes are believed to be separated by faults or suture zones, which are expected to be deep-reaching, but which may be difficult to observe at the surface. The resistivity model shows a clear transition in crustal properties across this region. Generally resistive upper crustal blocks are separated by well-resolved, anomalously conductive features that reach through the upper crust. They are spatially coincident with major surface fault zones, specifically the Bogd fault system, the Gobi–Tienshan fault system, and, to a lesser degree, the Trans-Altai fault system. Moreover, these features, which are well resolved by the dense MT site spacing, appear to be dipping slightly southwards, in agreement with geological estimates of fault dip. These features are interpreted as suture zones and tectonic boundaries between terranes or lithotectonic blocks. Therefore, the MT data support evidence for the division of Southern Mongolia into four principal tectonic zones, in agreement with other authors (e.g., Kröner et al. 2010; Guy et al. 2015), despite evidence for highly variable surface geology and multiple distinct lithostratigraphic domains (e.g., Badarch et al. 2002). We propose that fault zones congruent with the edges of these tectonic zones are natural boundaries, which is largely in agreement with tectonic zone boundaries previously determined by potential field methods (Guy et al. 2014).
The lower crust (20–45 km) is distinct, having a lower resistivity overall and several low-resistivity zones (~ 100 Ωm) below the Gobi–Altai and Trans-Altai zones. This is in agreement with studies that have argued for an allochthonous lower crust in this region, emplaced tectonically into its present position, that has been relaminated and metamorphosed (Guy et al. 2015; Kröner et al. 2010). We propose that future seismic data should be acquired here to provide alternative evidence of lithospheric structure.
The MT data indicate a thick lithosphere below Southern Mongolia (> 100 km), although penetration and resolution is limited at these depths. This is in contrast to the thin lithosphere (~ 70 km) previously reported below Central Mongolia (e.g., Petit et al. 2008; Comeau et al. 2018a), attributed to a local asthenospheric upwelling. Therefore, a steep lithospheric step is believed to exist, likely below the Gobi–Altai Mountains, highlighting the importance of this region as a major lithospheric boundary within the CAOB.
This research was financially supported by the DFG (Grant # BE 5149/6-1) and the SNF (Grant # 200021L_162660/1). MB is funded through a DFG Heisenberg Grant (5149/7-1, 5149/9-1). We thank Kerry Key for providing the 2-D MT inversion code. We thank the Geothermal Energy and Geofluids group at ETH Zurich for the use of their MT instruments in 2018 and the Geophysical Instrument Pool Potsdam for the use of their MT instruments in 2016 and 2017. We thank all those who helped collect the data and provided field support, especially our colleagues from the Institute of Astronomy and Geophysics at the Mongolian Academy of Sciences.
All authors were involved with the work. MJC helped collect the data, performed data processing, analysis, and modelling, interpreted the data, and prepared the manuscript. MB helped collect the data and assisted with the modelling and interpretation. JSK helped collect the data and performed data processing and analysis. AVG and AVK helped collect the data and assisted data analysis. ST and EB helped collect the data and supported field logistics. SD helped organize and manage field measurements. All authors read and approved the final manuscript.
This research was financially supported by the DFG (Grant # BE 5149/6-1) and the SNF (Grant # 200021L_162660/1). The funding bodies had no further role in the study design, data collection, data analysis, data interpretation, nor in the manuscript writing.
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The authors declare that they have no competing interests.
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