Thermochemical structure of the North China Craton from multi ...

Gondwana Research 37 (2016) 252–265

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Thermochemical structure of the North China Craton from multi-observable probabilistic inversion: Extent and causes of cratonic lithosphere modification Zhen Guo a,b, Juan Carlos Afonso b,⁎, Mehdi Tork Qashqai b, Yingjie Yang b, Y. John Chen a,c a b c

Institute of Theoretical and Applied Geophysics, School of Earth and Space Sciences, Peking University, Beijing, China ARC Centre of Excellence for Core to Crust Fluid Systems, Department of Earth and Planetary Sciences, Macquarie University, Sydney, New South Wales, Australia School of Oceanography, South University of Science and Technology of China, Shenzhen, China

a r t i c l e

i n f o

Article history: Received 20 March 2016 Received in revised form 22 June 2016 Accepted 9 July 2016 Available online 20 July 2016 Handling Editor: M. Santosh Keywords: Joint inversion North China Craton Ordos block Lithospheric thickness Sublithospheric convection Craton destruction

a b s t r a c t We present a 3D thermochemical model of the North China Craton (NCC) from the surface down to 350 km by jointly inverting surface wave phase velocity data, geoid height, surface heat flow and absolute elevation with a multi-observable probabilistic inversion method. Our model reveals a thin (~65–100 km) and chemically fertile lithosphere (87 b Mg# b 90) beneath the Eastern NCC, consistent with independent results from mantle xenoliths, and supports the idea that the Eastern NCC experienced significant lithospheric destruction and refertilization during the Phanerozoic. In contrast, beneath the Trans-North China Orogen, Inner Mongolia Suture Zone and Yinshan belt, we observe a more heterogeneous (chemically and thermally) lithosphere, indicating that these areas have been partly involved in lithospheric modification and mechanical erosion at multiple scales. A cold and chemically refractory (Mg# N 90) lithospheric mantle is imaged beneath the central TNCO and Ordos Block, reaching depths N260 km. This lithospheric “keel” is surrounded to the east by a high-temperature sublithospheric anomaly that originates at depths N 280 km. The spatial distribution of this anomaly and its correlation with the location of recent volcanism in the region suggest that the anomaly represents a deep mantle upwelling being diverted by the cratonic keel and spreading onto regions of shallow lithosphere. Our results indicate that the present-day thermochemical structure beneath the NCC is the result of a complex interaction between a large-scale return flow associated with the subduction of the Pacific slab and the shallow lithospheric structure. © 2016 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

1. Introduction Archean cratons are stable tectonic units typically with lithospheric thicknesses of ~ N 200 km, and usually underlain by refractory and buoyant subcontinental lithospheric mantle (SCLM) (Griffin et al., 2009). Cold temperatures, high viscosities, a compositional buoyancy associated with cratons are thought to be responsible for their longterm (billions of years) stability (Griffin et al., 2009). However, a number of studies have shown that lithospheric reactivation may take place at cratons, resulting in significant loss and/or modification of the SCLM (Gao et al., 2004; Zheng et al., 2007; Zhao et al., 2009; Zhu and Chen, 2011). The North China Craton (NCC, Fig. 1) is one of the best documented cases of cratonic SCLM modification (Menzies et al., 1993; Griffin et al., 1998; Gao et al., 2004; Zhu et al., 2012). Despite being one of the oldest cratons on Earth and having remained as a tectonically stable until the late Paleozoic, the eastern NCC underwent ⁎ Corresponding author. Tel.: +64 2 9850 8298. E-mail address: [email protected] (J.C. Afonso).

significant lithospheric rejuvenation resulting from tectonic activity from the Mesozoic to Cenozoic. This is manifested by the refertilized mantle xenoliths, development of basins, high values of surface heat flow, and extensive magmatism during that period (Griffin et al., 1998; Zheng et al., 2007; Zhu and Chen, 2011). In contrast to the significant lithospheric modification beneath the eastern NCC, the Ordos block in the western NCC is suggested to have remained stable and preserved thick lithosphere since the Precambrian (Griffin et al., 1998; Yang et al., 2008; Zhu and Chen, 2011; Zhu et al., 2012). The eastern and western NCC is separated by a sharp topographic break with an elevation of ~1500 m known as the North–South Gravity Lineament (NSGL) (Xu, 2007; Chen and Pei, 2010). This lineament coincides well with a rapid change in crustal thickness (Fig. 3d) and a significant gravity anomaly on the surface. Xu (2007) proposes that the NSGL is not only a shallow physical boundary but also a chemical boundary with an origin closely related to mantle processes triggered by the deeply subducted Pacific slab. However, this conclusion is drawn mainly from a comparison of basalts and xenoliths from a limited number of locations on both sides of the NSGL.

http://dx.doi.org/10.1016/j.gr.2016.07.002 1342-937X/© 2016 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Z. Guo et al. / Gondwana Research 37 (2016) 252–265

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Fig. 1. Geological setting of the North China Craton (NCC). NCC China is comprised of the eastern NCC (ENCC), the Trans-North China Orogen (TNCO) and the western NCC (WNCC). NSGL: North–South Gravity Lineament. The inset figure shows the major Precambrian cratons in China and location of the study region (modified after Santosh, 2010).

At present, there is no general agreement as to the actual causes, processes, and extent of lithospheric modification associated with the removal/modification of the SCLM beneath eastern NCC (Chen, 2010; Xu, 2007; Zheng et al., 2007; Yang et al., 2008; Zhu and Chen, 2011). Proposed geodynamic models include, but are not limited to, lithosphere delamination in response to the density instability of eclogite at the base of Archaean lower crust (Gao et al., 2004), thermomechanical erosion due to asthenospheric upwelling induced by the multiple subduction episodes during the Mesozoic (Xu, 2001; Zheng et al., 2007), and long-term influence of mantle plumes (Deng et al., 2004). In the past two decades, numerous geophysical studies have been conducted in the NCC in order to shed light on possible geodynamic mechanisms for the lithospheric modification of this region (Chen et al., 2004; Huang and Zhao, 2006; Chen and Pei, 2010; Zhu and Chen, 2011; Guo and Chen, 2016). Chen (2010) used P- and S-wave receiver functions to map the lithosphere–asthenosphere boundary (LAB). They observed a sharp change in LAB depth across the NSGL, from a thin lithosphere (b 100 km) beneath the eastern NCC to a thick lithosphere (≥200 km) beneath the western NCC. Chen et al. (2004) imaged a continuous high-velocity anomaly in the mantle transition zone (MTZ) beneath the eastern NCC, reaching as far as to the NSGL. They proposed that the high velocity anomaly is the stagnant remnants of the subducting Pacific plate, and the destruction of the ENCC is attributed to the mantle convection induced by the deep subduction of the Pacific plate (Chen et al., 2004; Huang and Zhao, 2006; Chen and Pei, 2010; Zhu and Chen, 2011). A more recent seismic tomography and anisotropy study revealed structures that could be interpreted as asthenospheric flow impinging on the basement of the NCC lithosphere (Zhao et al., 2009). Likewise, numerous studies on mantle xenoliths point to a widespread metasomatic/rejuvenation event since the Phanerozoic (Fan et al., 2000; Wu et al., 2005; Xu, 2007; Zheng et al., 2007). However, the spatial distribution of xenoliths is limited to the major faults in the NCC. Therefore, xenolith information cannot be used to obtain a 3-D model of the present thermal and chemical structure of the SCLM.

Seismic tomography, on the other hand, can be used to construct 3-D models of the velocity structure beneath the eastern NCC, but their conversion into temperature, density and/or compositional anomalies is plagued with difficulties and ambiguities (Goes, 2002; Shapiro, 2004; Yao et al., 2008; Afonso et al., 2013a, 2013b; Shan et al., 2014). For instance, when velocity anomalies from tomography models are converted into density anomalies, the gravity anomalies, induced mantle flow, topography, and plate velocities predicted by the density model tend to be poor representations of the real observations (Forte et al., 2007). In recent years, significant effort has been devoted to develop methods that can jointly invert different and complementary geophysical observations, such as seismic data, potential field data, topography, surface heat flow and others, for more realistic Earth models (van Gerven et al., 2004; Khan et al., 2008, 2013; Afonso et al., 2013a, 2013b; Shan et al., 2014). The main objective of this study is to construct a high-resolution thermochemical model of the lithosphere beneath the central and eastern NCC. We employ a recently developed multi-observable probabilistic inversion technique capable of jointly inverting high-quality surface wave measurements, potential fields, topography, and surface heat flow (Afonso et al., 2013a, 2013b). Based on this model, we address some fundamental questions as to the geodynamic evolution of the NCC region and its present thermochemical structure. 2. Geological setting The North China Craton (NCC) is located between the Central Asian Orogenic belt and the Yangtze Craton (Fig. 1), bounded by the Solonker suture to the north and the Qinling-Dabie-Sulu Orogenic belt to the south, respectively (Zhao et al., 2005; Santosh, 2010). The NCC is composed mainly of two major Archean to Paleoproterozoic blocks, the western (WNCC) and eastern blocks (ENCC), which are separated by the Trans-North China Orogen (TNCO) in between (Zhao et al., 2005). The western block (WNCC) can be further divided into the Ordos block and the Yinshan belt (YSB) (Santosh, 2010; Zhai and

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Santosh, 2011; Santosh et al., 2011a, 2011b; Zhai, 2014; Tang et al., 2015; Yang and Santosh, 2015; Yang et al., 2016). Based on the geological, geochemical, and seismic studies, Santosh (2010) suggested that the amalgamation between the YSB and the Ordos block occurred during ~ 1.95 Ga along the E-W trending Inner Mongolia Suture Zone (IMSZ) (Fig. 1). After that, the WNCC and ENCC assembled at ~1.85 Ga along the Trans-North China Orogen (Zhao et al., 2005; Santosh et al., 2006; Santosh, 2010; Zhai and Santosh, 2011). Since the late Paleozoic, the NCC has been affected by a series of subduction and continental collision events. To the south, the QinlingDabie-Sulu Orogenic belt was formed as a consequence of the Triassic collision and subduction of the Yangtze Craton beneath the NCC (Dong and Santosh, 2016). To the north, the Paleo-Asian Ocean closed along the Solonker suture in the Late Triassic and subsequent closure of the Mongol-Okhotsk Ocean along the Mongol–Okhotsk suture zone during the Middle Jurassic (~ 160 Ma) completed the final amalgamation between the Siberia Craton and NCC (Sengor et al., 1993; Xiao et al., 2003). The westward oblique subduction of the Paleo-Pacific plate since the late Mesozoic has been considered to be the primary geodynamic factor in the destruction of the cratonic lithosphere of the NCC (Chen, 2010; Zhu et al., 2012; Tang et al., 2013a,b; Y. Tang et al., 2013). Recent studies showed that the physical and chemical state of the mantle lithosphere beneath the ENCC changed significantly

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between Paleozoic and present times (Zhu et al., 2012). Xenolith samples from the Fuxian and Mengyin kimberlites, erupting in the early Paleozoic, suggest a cold (b40 mW/m2), thick and refractory lithosphere ~180–200 km thick existed beneath the NCC at the time of the eruptions (Menzies et al., 1993; Griffin et al., 1998; Zheng et al., 2007). However, the Cenozoic and Mesozoic xenoliths mainly indicate a fertile, hot (~ 65 mW/m2) and thin (b80 km) lithosphere in the ENCC (Yang et al., 2010), together with widespread igneous rocks (Wu et al., 2005; Tang et al., 2013a,b; Y. Tang et al., 2013), extensional structures and mineral deposits in the ENCC (He et al., 2016), leading to the hypothesis that the lithospheric mantle beneath the ENCC has been modified or destroyed during the Mesozoic/Cenozoic (Fan et al., 2000; Xu, 2007; Zheng et al., 2007; Yang et al., 2008; Chen, 2010; Yang et al., 2010). 3. Data and method 3.1. Data used in the joint inversion In this study, we utilize high resolution Rayleigh wave phase dispersion maps from the recent seismic tomography studies of Tang et al. (2013a,b), Y. Tang et al. (2013), Jiang et al. (2013), and Guo et al. (2013). The Rayleigh wave phase maps at 8–140 s periods of Tang et al. (2013a,b) and Y. Tang et al. (2013) are generated by using seismic

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Fig. 2. Rayleigh wave phase velocity maps at 30, 71, 100, and 125 s. Rayleigh wave data are from a combination of ambient noise tomography and two-plane surface wave tomography (Tang et al., 2012; Guo et al., 2013; Jiang et al., 2013). Black triangles show the locations of Cenozoic volcanoes in the study area.


data recorded by a total of 141 seismic stations, including permanent CEA (China Earthquake Administration) stations and portable stations of PKU and NCSA (North China Seismic Array). Short-period surface wave measurements at 8–40 s periods are extracted from ambient noise tomography (ANT), whereas long-period phase velocities at 25– 140 s periods are obtained by two-plane wave tomography (TPWT), which adopts 2-D sensitivity kernels to account for the finite frequency effects (Yang and Forsyth, 2006). Jiang et al. (2013) obtained surface wave measurements at 20–143 s periods from TPWT using teleseismic data recorded by the CEA and NCISP-VII array. To further improve the resolution in the shallow crust beneath the WNCC, phase velocity measurements from ANT of Guo et al. (2013) are also included in the joint inversion. The lateral resolution of these phase velocity maps are reported to be less than 200 km, with typical uncertainties of ~ 10 m/s at 10 s to ~ 80 m/s at 140 s (Guo et al., 2013; Jiang et al., 2013; Tang et al., 2013a,b; Y. Tang et al., 2013). The region between 109°E and 114°E is covered by more than one study and consequently surface wave dispersion datasets overlap. We have carefully compared phase velocities from three different studies (Guo et al., 2013; Jiang et al., 2013; Tang et al., 2013a,b; Y. Tang et al., 2013) in the overlapped region and only retained the data that are mutually coherent, that is, the data having phase velocity differences smaller than their individual standard deviations. Fig. S1 (see in Supplementary materials) shows dispersion curves

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from the three different tomography studies at two locations. Although different data, data processing and tomography methods are used among these studies, their reported dispersion curves agree well with each other in most cases. Thus, we average phase velocities of these three studies, based on the weights defined by their uncertainties within the overlapped region and overlapped period bands, to obtain a final set of phase dispersion curves at 8–140 s periods, which are used in the inversion of this study. Fig. 2 shows Rayleigh wave phase velocity maps at 30, 71, 100, and 125 s. The most prominent features in these maps are the strong low phase velocity in the northern TNCO, IMSZ, and eastern NCC, as well as high velocities in the Ordos Block in the WNCC. Low phase velocity is also observed in the Tanlu fault at 30–71 s. Surface heat flow (SHF) measurements are sparsely distributed in the northern and southern margins of the study region (Fig. 3a). A total of 85 measurements in the study area are taken from the literature (Hu et al., 2000). The estimated standard deviations are between 5– 15 mW m−2, based on the quality of the measurements. Following Shan et al. (2014), we first remove extreme values (b20 mW m− 2 and N 150 mW m− 2, black dots in Fig. 3a) thought to be affected by underground water flow and then interpolate the data onto a 1° × 1° grid. Although the data is sparse, the average SHF in the WNCC and the southern TNCO seems to be lower than that in the ENCC, where the average SHF is ~ 70 mW m−2, including peak values of

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Fig. 3. Geophysical data used in the multi-observable probabilistic inversion. (a) surface heat flow measurements (Hu et al., 2000); (b) filtered topography (https://lta.cr.usgs.gov/ GTOPO30) with wavelengths less than 50 km removed; (c) geoid heights from the EGM2008 model (Pavlis et al., 2012); (d) crustal thickness from He et al. (2014).

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~100 mW m−2. Some high SHF values are also found in the Shanxi rift within the TNCO. Geoid height data are taken from the Earth Geopotential Model EGM2008 (Pavlis et al., 2012), which includes spherical harmonic coefficients up to degree and order of 2190 (Fig. 3c). Since all masses within the Earth contribute to all harmonic degrees of the observed geoid, a high-pass filter needs to be applied to the complete geoid in order to remove the deep mantle signal, which is out of the scope of this work. Wavelengths N 4000 km (i.e. degrees 2–9) have therefore been removed from the complete geoid to retain the effects of density anomalies shallower than ∼ 400 km depth (Bowin, 2000). The mean values and associated variances are estimated from the global model for each 1° × 1° cell making up the model. The means represent the input data for each cell, while the variances are used to compute the standard deviation. The latter, however, are not true observational uncertainties, but rather a measure of the natural variability of the field within each cell. The maximum observed geoid height is located in the northern Trans-North China Orogen (TNCO ~ 4 m); standard deviations across the entire domain vary between 0.3 and 1.2 m. Elevation data are taken from the GTOPO30 dataset (https://lta.cr. usgs.gov/GTOPO30, Fig. 3b); a low-pass filter is applied to remove wavelengths b50 km. Estimates of the mean values and variances for elevation in each cell are obtained in the same way as for geoid heights. The data variability (as a standard deviation) within each cell ranges between 150–200 m. Our initial crustal model (Fig. 3d) was taken from the model of He et al. (2014), which is constrained by receiver function data obtained from a systematic analysis of ~ 800 temporal and permanent seismic stations in continental China. This initial model is subsequently updated during our inversion (see next section). 3.2. Multi-observable probabilistic inversion The multi-observable probabilistic inversion method used in this study has been described in detail in Afonso et al. (2013a, 2013b) and Shan et al. (2014). Therefore, in the following section, we only summarize aspects of the model parameterization and forward/inversion problem relevant to this study. The 3D volume of interest is subdivided into 104 non-overlapping columns with surface areas of 1° by 1°. We then invert surface wave dispersion curves, absolute elevation, geoid height, and surface heat flow in each of the constituent 1D columns. All 3D models discussed in this contribution are then obtained by assembling the solutions from the columns. The forward problems involve solving the 1D steady-state heat transport equation, minimizing the Gibbs freeenergy of the system, fitting geoid height and elevation under the 1D approximation, and computing Rayleigh wave dispersion curves (Afonso et al., 2013b). Lithospheric (conductive) geotherms are obtained from the steady-state heat transfer equation subject to Dirichlet boundary conditions at the surface of the model (TS = 10 °C) and at the bottom of the lithosphere (TLAB = 1250 °C). In the sublithospheric upper mantle, temperature profiles are not forced to be conductive but obtained directly from the inversion; a continuous temperature profile is obtained by linear interpolation between the inverted nodes. The choice of defining the base of the lithosphere as an isotherm is a common and practical option in lithospheric modeling and related to the fact that the lithosphere is a thermal boundary layer (cf. Afonso et al., 2016). The actual value of 1250 °C is chosen based on results from numerical simulations of small-scale convection with realistic viscosities (e.g., Zlotnik et al., 2008; Afonso et al., 2008; Ballmer et al., 2011), petrological evidence (Griffin et al., 2009), and recent thermochemical inversions (e.g. Shan et al., 2014; Afonso et al., 2016). All these lines of evidence suggest that isotherms b ~ 1250 °C tend to be dominated by conduction over long time-scales whereas those with temperatures above this value tend to be dominated by advection.

Stable mineral assemblages within the upper mantle and their relevant bulk properties (density, seismic speeds, etc.) are computed using a Gibbs free-energy minimization algorithm (e.g. Connolly, 2009) within the CFMAS system (CaO–FeO–MgO–Al2O3–SiO2). This guarantees that the physical parameters needed to solve the forward problems and predict different geophysical observables are thermodynamically consistent. For crustal layers, however, we relate bulk density to Vp and Vs assuming the validity of Birch's law of correspondent states (cf. Karato, 2008). As in Shan et al. (2014), surface wave dispersion curves are computed using a modified version of the code disp96 (Herrmann, 2002) and attenuation effects on dispersion due to temperature-dependent anelasticity are considered (Jackson and Faul, 2010). We parameterize the crust into one sedimentary and two crystalline layers. Each layer is characterized by constant values of thermal expansion, compressibility and thermal conductivity, whereas their bulk density, volumetric radiogenic heat production (RHP), total thickness and Vp/Vs ratio are obtained from the inversion (Afonso et al., 2013a). The initial sedimentary thickness is taken from the CRUST2.0 model (Laske et al., 2000) and the total crustal thickness is allowed to vary ± 5 km from the starting model constrained by the receiver function study of He et al. (2014). The parameterization used in the upper mantle follows that of Afonso et al. (2013b) and Shan et al. (2014), and we refer the reader to that work for details. In terms of the mantle compositional structure, here we only invert for the average bulk compositions of the lithosphere and sublithospheric upper mantle (i.e. the lithospheric and sublithospheric upper mantle are treated as independent compositional layers). All the variables used in the inversion and their a priori distributions are listed in Table 1. We employ a Bayesian inference approach to solve the inversion problem (Afonso et al., 2013a, 2013b). In a Bayesian framework, the solution to the inverse problem is given by a joint probability density function (PDF) in the parameter and data space, known as the posterior PDF, which contains the ensemble of acceptable models as allowed by data and a prior information (Shan et al., 2014). Since there is no

Table 1 Parameters and priors used in the inversion. Parameter

Range

References

Crust Density ρ1 Density ρ2 Density ρ3 Vp/Vs1 Vp/Vs2 Vp/Vs3 Thickness variation Δh1 Thickness variation Δh2 Thickness variation Δh3 RHP

2100–2700 kg/m3 2400–2950 kg/m3 2700–3150 kg/m3 1.65–2.2 1.65–1.85 1.65–1.85 −5.0–5.0 km −7.0–7.0 km −5.0–5.0 km 0.4–1.8 μW m−3

Rudnick and Gao (2014) Rudnick and Gao (2014) Rudnick and Gao (2014) Shan et al. (2014) Shan et al. (2014) Shan et al. (2014) Laske et al. (2000) Laske et al. (2000) He et al. (2014) Shan et al. (2014)

Lithospheric mantle LAB Al2O3 FeO MgO CaO

50–320 km 0.5–5.0 wt.% 6.0–9.2 wt.% 34.0–55.0 wt.% 0.1–5.5 wt.%

Chen (2010) Afonso et al. (2013a, 2013b) Afonso et al. (2013a, 2013b) Afonso et al. (2013a, 2013b) Afonso et al. (2013a, 2013b)

Sub-lithospheric mantle Al2O3 FeO MgO CaO TBuffer Tint(°C) Tbottom(°C)

2.0–5.0 wt.% 6.0–9.2 wt.% 34.0–55.0 wt.% 0.1–5.5 wt.% 1100–1500 °C 1200–1650 °C 1300–1650 °C

Afonso et Afonso et Afonso et Afonso et Afonso et Afonso et Afonso et

RHP: radiogenic heat production. LAB: Lithosphere-asthenosphere boundary.

al. (2013a, 2013b) al. (2013a, 2013b) al. (2013a, 2013b) al. (2013a, 2013b) al. (2013a, 2013b) al. (2013a, 2013b) al. (2013a, 2013b)


closed-form solution for the posterior, we use a Markov Chain Monte Carlo (MCMC) scheme to sample the posterior distribution. The MCMC scheme is driven by the Delayed Rejection Adaptive Metropolis (DRAM) algorithm (Shan et al., 2014; Guo et al., 2015). 4. Main results Predicted data from the multi-observable probabilistic inversion are shown in Fig. 4 (can be compared with the data in Fig. 3) as the means of their respective posterior PDFs. To further illustrate the data fits, several examples of the complete PDF of predicted data at specific locations in the Ordos block, ENCC, and northern Trans-North China Orogen are shown in Fig. 5. These locations are chosen because they span the entire range of total misfits, from excellent joint fits (Fig. 5a-d) to relatively poor ones (Fig. 5i-l). We note, however, that all predicted phase dispersion curves fit well the observed ones and other predicted data is within 2 standard deviations of the observed data in over 90% of the study region, with only few localities of relatively poor fit (e.g. Figs. 5i and k, 4). The resulting LAB depth map as defined by TLAB = 1250 °C is shown in Fig. 6a. A relatively shallow and flat LAB is seen beneath the ENCC and northern TNCO, ranging between ~65 and ~90 km depth, in good agreement with previous receiver function studies (Chen, 2010; Guo et al., 2012). The predicted LAB depth (~70 km) beneath the Datong volcanic area is similar to that inferred from the analysis of alkali basalts (Xu

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et al., 2005). An abrupt change in lithospheric thickness occurs beneath the central TNCO and the IMSZ where the LAB reaches up to ~ 260 km depth beneath the Ordos block, roughly consistent with a previous estimate based on S-wave receiver function (Chen, 2010). Instead of providing all five major oxides (CaO–FeO–MgO–A2O3– SiO2), we summarize compositional results by showing the lithospheric magnesium Mg# (Mg# = 100 × MgO/(MgO + FeO)) in Fig. 6c. The Mg# is an effective indicator of the extent of fertility or depletion in the mantle. High Mg# (N90) corresponds to refractory, depleted mantle that has experienced significant melt extraction, whereas low Mg# (b90) are considered to indicate either fertile or refertilized (e.g. melt metasomatism) mantle. We observe a clear correlation between the lithospheric Mg# and the main tectonic provinces as defined by surface features (Fig. 6c). The ENCC is characterized by relatively high values of FeO, Al2O3, and CaO (see Fig. S2 in Supplementary materials) and therefore low Mg# (87–88). Beneath the IMSZ and YSB, the lithospheric Mg# varies between 88 and 89.5. On the contrary, there is a noticeable tendency for higher Mg# in the central TNCO and Ordos block relative to the ENCC and IMSZ (89.5–91). The estimated uncertainty (as 1σ from their posterior distributions) in lithospheric Mg# is less than 0.8 in most of the study region (Fig. 6d), suggesting that the actual highs and lows are relatively robust features. However, the transitional regions between these highs and lows are more uncertain. With this caveat, we note the correlation between high/low topography and

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Fig. 4. Same as Fig. 3 but showing the predicted data from the inversion (as the mean values from the entire posterior PDF).


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Fig. 5. Examples of posterior histograms for topography, geoid, and SHF (gray) in the Ordos, the ENCC, and the northern TNCO. Red solid lines and blue shade indicate the observed data and their standard errors, respectively. Observed surface wave dispersion curves (red) and associated error bars are plotted with the predicted surface wave dispersion curves (gray lines) in the last column. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

high/low lithospheric Mg# across the NSGL, which highlights the role of the lithospheric mantle composition and thermal structure in explaining the current topography of the NCC. Below we provide independent evidence to support this view. While the composition of the sublithospheric mantle is allowed to vary during the inversion, the sensitivity to compositional variations within the sublithospheric mantle is very low (particularly at depths N200 km) given the current combination of inverted observables. Sensitivity to temperature, on the other hand, is significantly higher (cf. Afonso et al., 2013a, 2013b, 2016). Therefore, in what follows, we focus on temperature anomalies only when discussing the structure of the sublithospheric mantle. Fig. 7 summarizes the posterior distributions of geotherms as well as the wet and dry peridotite solidus. The general temperature structure correlates well with the main tectonic units. For example, high temperatures are inferred beneath the ENCC and the northern TNCO. The highest temperature is close to the dry peridotite solidus, at a depth of 85 km, beneath the northern TNCO, which strongly supports the presence of partial melting there (Xu et al., 2005). We infer low temperatures throughout the lithospheric mantle beneath the Ordos block (~650 °C at a depth of 60 km and ~900 °C at 100 km depth), compatible with geotherms inferred in other Archean cratons worldwide, such as the Western Australian Craton (Goes et al., 2005) and Slave Craton (Russell and Kopylova, 1999). Subsurface temperatures at different depths are shown in Fig. 8 as horizontal slices. In the lower crust (Fig. 8a), widespread high temperatures (~620 °C) show close relation with the late Mesozoic and Cenozoic extended/rift zones, such as the ENCC, the Shanxi rift in the TNCO, and the Hetao rift in the IMSZ. Low temperatures are imaged beneath the Ordos block and central TNCO, consistent with the observed high Pn and Sn velocities beneath these areas (Pei et al., 2007). In the upper mantle, we observe strong lateral temperature heterogeneities. Peak-to-peak temperature differences are ~ 500 °C at the

depth range of 60 and 120 km (Fig. 8b and c) and ~ 200 °C at 200 km depth. Large-scale low temperature beneath the Ordos block and central TNCO (Fig. 8b-d) extends down to ~ 300 km (Fig. 9), consistent with the recent seismic tomographic results, which shows a continuous high velocity in the upper mantle (Zhao et al., 2009). Surrounding the Ordos block and the central TNCO, high temperatures are imaged beneath the ENCC, the northern segments of the TNCO, and the YSB and IMSZ between 60 and 150 km (Fig. 8b and c). At 200 km depth (Fig. 8d), high temperatures are confined to a narrow, north–south trending corridor beneath the eastern TNCO, and broadens slightly towards the north beneath the eastern IMSZ and YSB. High temperatures in the upper mantle (Fig. 8c, d) also show a close correlation with the locations of Cenozoic volcanoes in the NCC. High temperatures are confined to the upper ~150 km beneath the volcanoes in the ENCC, such as the Shanwang and Wudi volcanoes near the Tanlu faults (Fig. 8d). On the other hand, high temperature anomalies can be traced down to at least 200 km beneath volcanoes in the TNCO and IMSZ, such as the Datong and the Hebi volcanoes in the northern and eastern TNCO, respectively (Fig. 8d). In order to depict more clearly the 3D structure of these sublithospheric high-temperature anomalies, we plot three vertical temperature profiles in Fig. 9 (see Fig. 6a for location) and 3D rendering in Fig. 10. Corresponding density anomalies are also shown for comparison. In all the vertical profiles, the high temperature and buoyant anomalies in the sublithospheric mantle show a clear convective-like structure, tend to focus along regions characterized by thin lithosphere (as expected if they are indeed convective features), and correlate well with the location of surface volcanism. This convection pattern also results in conspicuous inverted temperature profiles beneath locations where upwellings interact with the overlying lithosphere (e.g. Figs. 7c, d and 8a, b). Although such inverted geotherms cannot be obtained in traditional thermal studies of the lithosphere–asthenosphere system, they are common in upper mantle convection studies and highlight the benefit of our method.


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The eastward-tilted high temperature anomaly (low density) beneath the TNCO (Fig. 9c and d) extends from depths N250 km beneath the easternmost parts of the Ordos block to ~ 80 km depth, beneath the Cenozoic Hebi volcano (~ 4 Ma). From the actual 3D thermal structure, it is likely that this high temperature anomaly has an important north–south velocity component as well at this location, allowing lateral flow from the two main upwellings at the north and south ends of the anomaly (e.g. Figs. 8 and 10). We also note that the thermal structure imaged in Fig. 9e-f is reminiscent of a small convection cell (i.e. coupled upwelling-downwelling). Forced downwellings of material from the bottom of the lithosphere in response to active upwellings is a ubiquitous feature in thermomechanical simulations (e.g. Sleep, 1994; Agrusta et al., 2013), but they are difficult to image using traditional tomography. We discuss this further below. 5. Discussion The resulting thermochemical model shows that the ENCC is underlain by thin lithosphere (~ b 100 km), with a fertile average bulk composition (Mg# ~ 88). This observation is consistent with independent estimates of lithospheric geotherms and compositions revealed

by mantle xenoliths contained in the Neogene (~16–5 Ma) Shanwang basalts (Fig. 11). The P–T conditions from these peridotite xenoliths were estimated using the Grt-Opx thermos-barometer of Brey and Kohler (1990) and point to equilibration pressures and temperatures of ~1.6–2.4 GPa and ~1000–1180 °C, respectively (Zheng et al., 2006, 2007). This suggests that these xenoliths were extracted from shallow, yet hot levels (50–80 km depth), close to the LAB (Figs. 7, 8). We emphasize here that despite the excellent agreement between xenolithbased and inverted geotherms, our inversion does not use local xenolith information as a constraint (cf. Afonso et al., 2013a); inverted compositions emerge naturally from the thermodynamically -constrained inversion of geophysical data only. In this context, it is interesting that the Mengyin garnet peridotite xenoliths, included in early Paleozoic (457–500 Ma) kimberlites, sampled a chemically refractory lithospheric mantle, with Mg# between 92 and 93 (Zheng et al., 2007), whereas our inverted values suggest a more fertile present-day value (87 b Mg# b 90) (Fig. 11). The estimated P–T conditions from two well-studied Mengyin samples are 56–60 kbar (180–200 km) and ~1100 °C, and fall near a geotherm corresponding to surface heat flow of 40 mW/m2 (Zheng et al., 2006). This suggests a thick and cold lithosphere beneath the ENCC during the Paleozoic (Zheng et al., 2007), similar to the inverted temperature

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beneath the Ordos (Fig. 7). These striking differences between estimates from xenolith studies and from our inversion strongly support the idea that most of the ENCC experienced substantial modification since the Paleozoic. More importantly, our results indicate that the lithospheric modification not only removed more than 100 km of lithospheric mantle (and associated crustal thinning), but also altered the composition significantly. This is expected in the regions with thinned lithospheres where partial melts from the uprising asthenosphere percolate and react with the shallow remnant of the lithospheric mantle, imparting a fertile character to it via melt metasomatism (refertilization) (Piccardo, 2008; O'Reilly and Griffin, 2012). When combined, all these observations explain well the observed low topography (i.e. fertile, dense lithosphere) and positive gravity anomalies of ENCC. Although in most cases the inverted Mg# are consistent with the those observed in “recent” mantle xenoliths, a noticeable exception occurs in the Hebi region, located in the boundary between the TNCO and ENCC (Fig. 11). Although the high equilibration temperatures and no garnet from the peridotitic mantle xenoliths contained in lavas from the Hebi volcanos (~ 4 Ma) suggest a thin and hot lithospheric mantle (Zheng et al., 2007; Sun et al., 2012), similar to our results, a significant population of xenoliths exhibit a more refractory, high Mg# character. This, however, is not surprising, as it is likely that shallow refractory relics have been preserved locally beneath Archean regions that experienced mantle metasomatism/modification. Indeed, this is the interpretation that Zheng et al. (2007) gave to the refractory suite contained in the Hebei lavas. Such interpretation is also consistent with our results for the present-day lithospheric thickness and geotherm beneath this region, as well as with the proximity of the

Hebi volcanoes to the cold, thick lithosphere Ordos block (Fig. 6a). In fact, this region is at the boundary between refractory and fertile lithospheric domains (Fig. 6c), and therefore the existence of local depleted remnants at shallow depths is highly likely. The inconsistency between our results and those from limited xenolith samples thus illustrate the advantages and limitations of both mantle xenoliths and multiobservable probabilistic inversion to probe the lithospheric mantle. While mantle xenoliths are spatially restricted and can be biased by local heterogeneities in the lithosphere, our inversion method is less sensitive to such heterogeneities, offers a more continuous picture, and targets large-volume averages of the bulk composition. Furthermore, our method is restricted to present-day estimates, whereas xenoliths can sometimes offer samples of the underlying mantle over time. To the west of the NSGL, our results reveal a more heterogeneous lithosphere, both chemically and thermally. A relatively shallow LAB and high temperatures in the upper mantle are inferred beneath the northern TNCO, IMSZ and YSB, consistent with the widespread Cenozoic volcanism, rifting, and extensive seismicity in these areas (Xu, 2007). Chemically, both fertile (Mg# ~88) and relatively less-depleted (Mg# ≥ 90) lithospheric mantle are inferred beneath these areas. Our predicted distribution for lithospheric Mg# in the northern end of the TNCO again overlaps with the observed distribution in mantle xenoliths from the Neogene Hannuoba volcanism (Fig. 11). The central TNCO and Ordos block, on the other hand, are characterized by thick (≥160 km) and relatively depleted mantle lithosphere (Mg# N 90) with cold mantle geotherms in the upper 300 km (Figs. 6 and 9). The striking differences in the thermal and chemical structure across the NSGL revealed by our results indicate that the NSGL is a lithospheric-scale physical and chemical boundary that separates the NCC (Xu, 2007). Our results also suggest that the lithospheric mantle beneath eastern and western NCC experienced different degrees of thermal and/or chemical modification. To the east of the NSGL, the lithospheric mantle has been substantially modified both chemically and physically. To the west of the NSGL, however, the northern segments of the WNCC and TNCO have been partly involved in lithospheric refertilization and mechanical erosion during the Phanerozoic, with regions of relatively high Mg# perhaps reflecting remains of the original Archean lithosphere (Zheng et al., 2007). The central TNCO and Ordos block seemed to have preserved their original cratonic lithosphere. One of the most intriguing features revealed by our study is the high temperature anomaly surrounding the thick lithosphere beneath the central TNCO (Figs. 8–10). Its spatial distribution closely follows the abrupt change in lithospheric thickness and surface distribution of Cenozoic intraplate volcanic fields (Figs. 6, 8 and 9). Geochemical studies show that the alkaline basalts at these intraplate volcanoes were originated from asthenospheric melting and developed in an extensional regime (Xu et al., 2005; Xu, 2007). Recent tomographic images show a continuous high velocity in the mantle transition zone, which is typically interpreted as the stagnant Pacific slab with its edge reaching as far as the NSGL (Huang and Zhao, 2006). Receiver function studies also suggest an overall thickened mantle transition zone beneath the ENCC, in agreement with the idea of a stagnant slab (Chen, 2010). If this is the case, the replacement of deep mantle materials would create a mass-conserving return flow around it (e.g. Faccenna et al., 2010). Whereas the actual pattern of the return flow depends on the 3-D structure of the subducting plate, a persistent feature in numerical simulations of subduction is the upwelling of hotter deep material around the leading edge of the subducted slab that bends at shallower depths towards the trench (Faccenna and Becker, 2010; Faccenna et al., 2010; Afonso and Zlotnik, 2011; Moresi et al., 2014). This creates a large-scale sublithospheric mantle circulation pattern that would interact with the lithosphere at shallow depths and likely promote smaller-scale instabilities and lithospheric erosion (Sleep, 1994; Agrusta et al., 2013; Guo et al., 2016).


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Fig. 8. Temperature slices of the NCC at different depths. These maps depict the means of the actual posterior distributions. Black triangles show the locations of Cenozoic volcanoes in the study area.

The actual 3-D distribution of the high temperature anomaly imaged by our method suggests a connection with a deeper upwelling, supported by its amplitude, its correlation with recent volcanism with OIB (Ocean Island Basalts) signature (Xu et al., 2005; Xu, 2007), and its spatial association with the edges of the cratonic keel. In this scenario, the upwelling flow would be forced to bend around the cratonic keel and channeled towards the regions of thinner lithosphere (e.g. east TNCO, ENCC), right beneath the Cenozoic volcanoes in the TNCO (Fig. 9). This in turn would lead to smaller-scale convection patterns (e.g. Fig. 9c) in the shallow sublithospheric mantle and partial melting, which could reach shallower depths along local lithospheric discontinuities and finally feed the Cenozoic intraplate volcanoes in the TNCO. We note that the plausibility of such scenario has been demonstrated in a number of studies using numerical simulations (e.g. Sobolev et al., 2011). In this context, we also note that a bodywave tomography study (Zhao et al., 2009) reveals a strong slow velocity anomaly, similar to the high temperature anomaly imaged in this study, can be traced down to at least transition zone depths. Also, SKS splitting analyses show striking changes in the fast polarization directions and delay-time parameters in the WNCC, TNCO and ENCC, implying a complex upper mantle convection pattern (Zhao et al., 2011).

Numerical modeling shows that, in some cases, sub-lithospheric convection can induce significant basal erosion (e.g. Sleep, 1994; Sobolev et al., 2011; Wallner and Schmelling, 2016). This process would be significantly intensified by the presence of a preexisting weak zone in the cratonic lithosphere. Chen et al. (2014) recently identify an intra-lithospheric interface beneath the Ordos block at the depth of 80 km, which has been interpreted as a mechanically weak layer. The intrinsic weakness of such layer would make it vulnerable to thermal perturbations and strain focusing, hence facilitating the thermal and chemical modification of the lithospheric mantle (Chen et al., 2014). The thermochemical erosion induced by the multi-scale convection pattern proposed here is most likely an on-going process that is modifying the lithospheric mantle beneath the TNCO, which may finally lead to the gravitational instability and destruction of the lower part of the lithosphere. Such large-scale lithospheric foundering, triggered by the replacement of relatively cold shallow mantle with hot and buoyant sublithospheric material, is a globally significant process. It has been proposed to occur in many parts of the world based on numerical simulations and/or tomography models (e.g. Puna Plateau, Southern Sierra Nevada, Siberian Traps; Tanton and Hager, 2000; Boyd et al., 2004; Levander et al., 2011; Beck et al., 2015). Based on our results, it seems possible that the destruction of the lithospheric

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mantle beneath ENCC represents only an early stage of a much larger event that may involve the future destruction/modification of much of the NCC. 6. Conclusions We present an integrated thermochemical model of the NCC by jointly inverting surface heat flow data, surface wave dispersion curves, geoid height and absolute elevation with a multi-observable, probabilistic and thermodynamically-consistent inversion method. We confirm the widespread lithospheric modification of the ENCC inferred in previous studies and map the extent of this mechanical and chemical alterations. Our study reveals a thin (~ b 100 km) and chemically fertile lithosphere beneath the Eastern NCC, in agreement with independent xenolith evidence. In contrast, the lithosphere beneath the TNCO and WNCC is characterized by a more heterogeneous constitution both in their thermal and compositional structures. A clear lithospheric “keel” is imaged down to ~ 270 km depth in the central TNCO and Ordos block, but its extension does not follow the boundaries of

known tectonic provinces, possibly indicating a significant modification of the deep lithosphere that occurred after the tectonic processes that created the surface features. In general, we find that a non-intuitive combination of chemical and thermal structure is required to simultaneously explain all the constraining data. This highlights the importance of lithospheric structure in controlling the signatures of surface observables. A sub-lithospheric high temperature anomaly is imaged beneath and around the cratonic keel of the Western NCC and its distribution correlates well with the location of recent volcanism in the region. This anomaly seems to be related to the upwelling of sublithospheric material, which creates forced downwellings and erosion of the basal parts of the lithosphere. The juxtaposition of relatively cold lithospheric mantle with hot sublithospheric material around the central TNCO and Ordos block is dynamically unstable and may result in the future convective removal of a significant part of the lithospheric mantle beneath the TNCO. Based on the spatial characteristics of this anomaly, we propose that it is the result of a complex interaction between a largescale upwelling associated with the subduction of the Pacific plate and


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Acknowledgements We thank M. Santosh, T. Gerya and an anonymous reviewer, for constructive comments that significantly improved the manuscript. We also thank Dr. Youcai Tang and Dr. Mingming Jiang who provided their surface wave phase velocity measurements. JCA and YY were supported by an ARC Discovery Project (DP120102372). GZ and YY are also supported by Australian Research Council Future Fellowship (FT130101220). This is contribution 824 from the ARC Centre of Excellence for Core to Crust Fluid Systems (http://www.ccfs.mq.edu. au) and 1089 in the GEMOC Key Centre (http://www.gemoc.mq.edu. au).

Appendix A. Supplementary data Fig. 10. 3D rendering of the thermal field beneath the study region. The shown isosurface enclose temperatures N1330 °C; its color scale indicates depth. Two main deep upwellings can be seen at the northern and southern ends of the high-temperature anomalies in Fig. 8c-d. These main upwellings are laterally connected at shallower depths by regions of, presumably, lateral flow also visible in Fig. 8d. See text for more details.

Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gr.2016.07.002.

the shallow lithospheric structure. This complex interaction may also be responsible for multi-scale mass and energy processes between the lithosphere and sublithospheric upper mantle, which explains the

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