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Keywords:

  • seismic imaging;
  • receiver functions;
  • High Lava Plains;
  • Pacific Northwest;
  • Owyhee Plateau

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[1] We analyze teleseismic P-to-S receiver functions to image crustal structure beneath the High Lava Plains (HLP) of eastern Oregon and surrounding regions. Coverage from 206 broadband seismic stations provides the first opportunity to resolve variations in crustal composition, thickness, and heterogeneity on scales of a few km in depth and tens of km laterally across the HLP region. We utilize both Hκ stacking and a new Gaussian-weighted common conversion point stacking technique. We find crust that is ≥40 km thick beneath the Cascades, Idaho Batholith, and Owyhee Plateau and thinner (∼31 km) crust beneath the HLP and northern Great Basin. Low Poisson's ratios of ∼0.240 characterize the granitic crust beneath the Idaho Batholith, while the Owyhee Plateau exhibits values of ∼0.270, typical of average continental crust. The Owyhee Plateau is a thick simple crustal block with distinct edges at depth. The western HLP exhibits high average values of 0.304, typical for regions of widespread basaltic volcanism. Combined with other geological and geophysical observations, the areas of abnormally high Poisson's ratios (∼0.320) and low-velocity zones in the crust beneath north-central and southern Oregon are consistent with the presence of partial melt on either side of the HLP trend, suggesting a central zone where crustal melts have drained to the surface, perhaps enabled by the Brothers Fault Zone. Thicker crust and an anomalous N-S band of low Poisson's ratios (∼0.252) skirting the Steens Mountain escarpment is consistent with residuum from a midcrustal magma source of the massive flood basalts, supporting the view of extensive mafic underplating and intraplating of the crust from Cenozoic volcanism.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[2] The extent and volume of the back-arc volcanism in the Pacific Northwest, United States, as well as its occurrence within the continent, makes the Cascadia subduction system unique. Subduction along the western margin of North America has been active since the Triassic [Dickinson, 2004]. Accretion of Mesozoic and early Cenozoic allochthonous terranes onto the western margin of Precambrian North America formed the foundation of the crust in the Pacific Northwest [Coney et al., 1980]. This boundary is often delineated by sharp gradients in 87Sr/86Sr isotope initial ratios (isopleths of 0.704 and 0.706 are hereafter referred to as the “0.704” and “0.706” lines) [Armstrong et al., 1977]. The terranes have varying composition, ranging from oceanic fore-arc basins [Dickinson, 1979] and island arcs [Gray and Oldow, 2005] to fragments of continental crust [Coney et al., 1980]. Large-scale extension of the western United States beginning in the mid-Tertiary was accompanied by the onset of widespread magmatism typified by rhyolitic ignimbrites, ash flow tuffs, and mostly rhyolitic lava flows [Lipman et al., 1972; Noble, 1972; Armstrong, 1978]. Magmatism in the Pacific Northwest includes not only Cascade arc volcanism, but also widespread and voluminous volcanism east of the arc, including the Columbia River and Steens flood basalts (Figure 1). The origin of the back-arc magmatism remains a contentious subject of debate [e.g., Carlson and Hart, 1987; Camp and Ross, 2004; Jordan et al., 2004; Hales et al., 2005].

image

Figure 1. Geologic and tectonic map of the Pacific Northwest, United States. The Juan de Fuca plate (JdF), North American plate (NA), McDermitt caldera (MC), Jordan Craters (JC), Diamond Craters (DC), Newberry Volcano (NB), Steens Mountain escarpment (SM), Harney Basin (HB), Brothers Fault Zone (BFZ), Oregon-Idaho graben (OIG), Monument (MDS) and Chief Joseph (CJDS) dike swarms and other geologic provinces are labeled. Mid-Miocene Steens and Columbia River flood basalt are shown as light brown shaded regions with overlain associated dike swarms [after Camp and Ross, 2004]. Areas of Quaternary basalt are shown in red. Locations of Holocene volcanism are denoted by triangles [Siebert and Simkin, 2002]. Isochrons of rhyolitic volcanism, as well as eruptive centers (gray dotted outlines), are shown across the High Lava Plains and Snake River Plain [Jordan et al., 2004; Pierce and Morgan, 1992]. Gray dashed line marks the boundary of the Precambrian Belt Basin [Harrison, 1972; Ross and Villeneuve, 2003]. Approximate locations of 87Sr/86Sr isopleths of 0.704 and 0.706 (“0.704” and “0.706” lines) are denoted by black dashed lines [after Armstrong et al., 1977; Kistler and Peterman, 1978; Leeman et al., 1992].

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[3] The High Lava Plains (HLP) region of eastern Oregon represents one of the largest, yet least understood, intraplate magmatic centers on Earth. It is characterized by voluminous mid-Miocene outpourings of the Steens and Columbia River flood basalts that erupted near the western edge of the craton [e.g., Carlson and Hart, 1987]. A period of extensive coeval rhyolitic and basaltic volcanism across central Oregon and Idaho followed the flood basalt event (Figure 1). Postflood basalt activity is marked by two semilinear time progressive tracks that both started in the area surrounding the Owyhee Plateau. One, propagating to the northeast with the direction and speed of North American plate motion, formed the Snake River Plain to the present-day actively volcanic Yellowstone area [Pierce and Morgan, 1992]. The other propagated northwest to Newberry Volcano, forming the High Lava Plains [MacLeod et al., 1976; Jordan et al., 2004]. In contrast to the rhyolites, the basalts along both tracks appear to have no spatial correlation with age [e.g., Draper, 1991]. The effects of regional late Cenozoic extension are evident in southern and central Oregon via well developed Basin and Range normal faulting. Basin and Range structure terminates at the southern edge of the Brothers Fault Zone, a series of NW striking, small displacement en echelon faults [e.g., Lawrence, 1976; Pezzopane and Weldon, 1993; Meigs et al., 2009] and extension across Oregon has been estimated to be ∼17% [Wells and Heller, 1988]. Results from paleomagnetic data analyses suggest the E-W trending Blue Mountains terrane has seen significant lateral translation and rotation since post-Cretaceous time [e.g., Riddihough et al., 1986; Housen and Dorsey, 2005]. Measurements of present-day deformation from GPS data indicate a pole of rotation on the Washington-Oregon border that is consistent with the extension in southern Oregon [McCaffrey et al., 2000].

[4] In this paper, we analyze receiver functions from teleseismic earthquakes recorded at broadband seismic stations in the region of central and eastern Oregon, southern Washington, western Idaho, and northern Nevada. The focus of our analysis is the first-order determination of variations in thickness and seismic properties of the crust beneath the region. These new constraints on crustal properties enable a better understanding of the consequences of extension and volcanism in modifying the crust of the HLP, and how those processes link to an improved understanding of regional tectonic evolution.

2. High Lava Plains Passive Seismic Experiment and Data Collection

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[5] Our data set for this study consists of teleseismic data from 206 broadband seismic stations within the High Lava Plains and surrounding regions that operated between 2004 and 2009 (Figure 2). The bulk of the recording stations were part of the High Lava Plains project [Carlson et al., 2005] in which 118 broadband stations, spaced 15–20 km apart, operated between January 2006 and September 2009 over a ∼220,000 km2 area across eastern Oregon, northern Nevada, and western Idaho. Sensors included nearly all Guralp 3T and Streckeisen STS-2 broadband seismometers, as well as three Guralp ESP and one 40T intermediate band seismometers from the IRIS PASSCAL, Carnegie Institution of Washington, and Arizona State University instrument pools. Stations continuously recorded data at 40 samples per second per channel using either a Reftek RT130 or Quanterra Q330 data logger. GPS timing was used throughout the network. The array was configured into two swaths, one NW-SE following the age progressive trend of the HLP eruptive centers, and one N-S from the northern Great Basin to the Blue Mountains (Figure 2). Station deployment occurred in stages, with the bulk of the array installed by the end of summer 2007, at which point 106 stations were simultaneously collecting data. Twelve of the seismometers were moved to new sites during summer 2008 to enhance regional coverage during the last year of the deployment.

image

Figure 2. Broadband seismic stations used for crustal receiver function analysis. White symbols denote station locations (squares, High Lava Plains array; triangles, USArray Transportable Array; circles, regional networks); solid black lines denote active source experiments used to obtain a priori crustal Vp for Hκ stacking. Dashed lines denote regions for which each average velocity profile (R1–R6b) was applied.

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[6] During the operating phase of the HLP array, broadband stations from several other networks throughout the Pacific Northwest, notably the EarthScope/USArray Transportable Array (USArray TA) and other regional networks, also recorded data. The majority of USArray TA stations in the vicinity of the HLP array operated between summer 2006 and fall 2008. The nominal spacing for USArray TA stations was ∼70 km and provided a coarse grid of stations around and within the denser HLP array to provide regional context for results from HLP data analyses.

[7] We used the National Earthquake Information Center (NEIC) monthly hypocenter catalog to select 1960 candidate earthquakes for analysis. We searched the catalog based on origin times between January 2004 and September 2009, epicentral distances between 30° and 95°, and mb ≥ 5.5. The list of earthquakes fitting these criteria was compiled and waveform data from the IRIS Data Management Center were obtained using the Standing Order for Data (SOD) software package [Owens et al., 2004]. The initial number of station-event pairs based on these criteria was 114,897. As a result of our data culling process, described below, we retained 14,356 seismograms from 849 events for our receiver function analysis (Table S1). The final data set provides excellent coverage from the NW and SE directions, including mostly distant events from the SW, and more scattered, sparser coverage from the NE (Figure 3).

image

Figure 3. Teleseismic earthquakes used for crustal receiver function analysis. Earthquakes with mb greater than 5.5 at distances 30°–95° from our stations are shown as gray circles; black star denotes center of seismic station coverage.

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3. Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

3.1. Receiver Function Estimation

[8] The receiver function method has become a commonly employed imaging technique used to study discontinuities in seismic wave speeds at crustal, lithospheric, and upper mantle scales. The technique relies on forward scattered P-to-S converted waves from seismic impedance boundaries beneath a single station. The receiver function itself is a time series that represents the approximate wavefield separation of SV energy from P energy on the radial component, where time is relative to the direct P wave arrival. The computation of a receiver function is accomplished through a deconvolution operation of the vertical component from the radial component [Langston, 1979]. Both vertical and radial seismograms are assumed to contain the same information related to the source time function, instrument response, and path effects through the lower mantle. Hence, this process isolates the radial Earth impulse response below the station and is often alternatively referred to as source equalization or normalization [Langston, 1979]. Deconvolution can be performed either in the frequency domain or the time domain. For this study, we chose to use the time domain iterative deconvolution method of Ligorria and Ammon [1999]. The advantage of this approach is that the signal produced is truly causal and is free from regularization methods such as water level stabilization [Clayton and Wiggins, 1976] in the frequency domain or damping parameters in time domain inversions [Sheehan et al., 1995].

[9] We follow the same general procedure for computing receiver functions as described by Eagar et al. [2010], with a few notable differences to enhance imaging of crustal structure. In this process, we cut the raw seismograms 40 s before and 135 s after the predicted P wave arrival based on the 1-D IASP91 velocity model [Kennett and Engdahl, 1991] and removed the mean and the first-order trend from the cut waveforms. The seismograms were filtered using a 0.02 Hz high pass and a 10% cosine taper. We then rotated the horizontal seismograms along the free surface to obtain radial and transverse components of motion. Receiver functions for each source-station pair were generated using iterative deconvolution [Ligorria and Ammon, 1999], a forward modeling procedure that predicts a receiver function using a series of Gaussian pulses convolved with the vertical seismogram, resulting in a predicted radial or transverse seismogram. The pulse width of the receiver function is determined by the Gaussian parameter [Ligorria and Ammon, 1999], which we set at 2.5. This results in a pulse width of ∼1 s (or ∼2 s dominant period) and is an effective low-pass filter typical of teleseismic crustal studies that results in ∼3.5 km vertical resolution. Receiver function preprocessing and computation were automated via batch processing on a 32 CPU computing cluster to significantly reduce computation time for the large data set presented here. While we computed both radial and transverse receiver functions, we focus on the results from the radial receiver functions in this study. We show example waveforms and resulting receiver functions from one station in Figure 4.

image

Figure 4. (left and middle) Seismograms and (right) computed receiver functions from a mb 6.1 Aleutian event on 16 April 2008. Approximate arrival times of Ps, PpPs, and PsPs phases are marked by arrows. Gray shaded waveforms in Figure 4 (right) denote positive arrivals.

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3.2. Hκ Stacking

[10] To determine average crustal properties, we analyzed receiver functions for each station using the stacking technique of Zhu and Kanamori [2000]. This method enables the determination of Moho depth (H) and the ratio of crustal P to S wave speeds (Vp/Vs, or κ) by treating the crust as a homogeneous, horizontal, isotropic layer over a half-space. The differential traveltime between the direct P and the primary conversion from the Moho (Ps) can be used to estimate crustal thickness; however, the PsP traveltime has an inherent tradeoff between the layer thickness and crustal seismic wave speeds [e.g., Ammon et al., 1990]. Zandt and Ammon [1995] showed that traveltime information of reverberations within the crust (PpPs and PsPs + PpSs, which we refer to just as PsPs) can help reduce the nonuniqueness of the velocity/thickness tradeoff. Figure 4 shows an example of approximate arrival times of the Ps, PpPs, and PsPs on individual receiver functions and their associated seismograms. To better constrain H and κ, assuming a locally horizontal discontinuity, Zhu and Kanamori [2000] introduced a method that utilizes these multiple crustal reverberations along with the Ps primary phase information. We rearrange the terms of the original equations given by Zhu and Kanamori [2000] to describe the relative arrival times for each of these phases as a function of both H and κ and also account for a spherical coordinate system by

  • equation image
  • equation image
  • equation image

where p is the ray parameter of the incident P wave in km/radian, R is the radius of Earth, and Vp is the average crustal P wave speed.

[11] The method for finding the optimal H and κ values to describe the crust is a grid-searching algorithm that maximizes the stacked amplitudes of Ps, PpPs, and PsPs. The parameters H and κ are varied between a range of values, and relative traveltimes for each phase are computed by equations (1)(3). For this study, we explored H ranges from 20 to 65 km using a step size of 0.01 km and κ ranges from 1.50 to 2.20 using a step size of 0.005. The amplitudes at the computed traveltimes of all receiver functions recorded by a single station are then summed using the stacking function

  • equation image

where Ai is the amplitude of the ith receiver function as a function of predicted traveltime and w1, w2, and w3 are weighting terms given to each of the respective phases. We note that the third term in equation (4) has a negative value due to the opposite polarity of PsPs. For this study, we usually defined w1, w2, and w3 as 0.5, 0.3, and 0.2, respectively, although we adjusted these values at a few stations (Data Set S1) based on a qualitative assessment of the visibility of the phases, described below. The best solution was determined where s(H, κ) was a maximum. We converted the Vp/Vs ratio beneath a station to Poisson's ratio (σ) using

  • equation image

for purposes of interpretation of rock material properties.

[12] The traveltimes used for crustal receiver function analysis are much less sensitive to Vp than to Vs [Zhu and Kanamori, 2000], and it is common to assume an average Vp for the entire crust. Previously obtained active source models in this region provide us with a priori estimates for crustal Vp averages (Table 1). We assigned an average Vp to each station (Figure 2) based on the proximity of stations to refraction lines, regional geologic boundaries, and preliminary results using a constant Vp. A comparison of results using a constant Vp versus regional Vp variations (Data Set S1) yielded an average difference of only ±0.7 km in Moho depth and ±0.006 in Vp/Vs. These differences are small enough not to affect the geologic interpretations of our results.

Table 1. Seismic Refraction Profiles Used for Regional Average Crustal Vpa
Refraction ProfileReferenceAverage Crustal Vp (km/s)
  • a

    Average Vp calculated from locations near center of regions defined in Figure 2.

R1Leaver et al. [1984]6.55
R2Catchings and Mooney [1988a]6.41
R3Catchings and Mooney [1988b]6.44
R4aCox and Keller (manuscript in preparation, 2011)6.10
R4bCox and Keller (manuscript in preparation, 2011)6.29
R5aLerch et al. [2007]6.19
R5bLerch et al. [2007]6.36
R6aHill and Pakiser [1967]6.13
R6bHill and Pakiser [1967]6.27

[13] There are several benefits of the Hκ grid-searching analysis, as well as a few limitations to consider given the assumptions necessary to perform Hκ analysis. For instance, stacking receiver functions from many events from all azimuths and epicentral distances at a given seismic station enables the determination of an average crustal structure in the vicinity of each station. This provides for comparison of results at different stations that were not necessarily deployed in the same time period. Another benefit is that the Hκ analysis does not require manual picking of arrival times of converted phases, which can be difficult given the low amplitudes of the primary and multiple converted phases relative to the direct P on a single record. Removing the restrictions of manual picking also enables many components of the analysis to be readily automated [e.g., Crotwell and Owens, 2005]. We note that the largest limitation to this stacking method is that complex crustal structures, such as anisotropy, dipping or sharply varying Moho, or other strong velocity contrasts (i.e., near-surface sedimentary layers or midcrustal layers) can incorrectly bias the estimates of Moho depth and Vp/Vs ratio.

[14] To estimate uncertainties in the final stacking solution, we constructed standard deviation contours in s(H, equation image). These contours are defined by 1 − equation image, where σ2 is the variance and N is the number of waveforms [Eaton et al., 2006]. There is a separate family of uncertainties that is more difficult to quantify. In particular, the initial choice of Vp shifts the final Hκ value; thus choosing Vp based on other local constraints where available is important. Finally, this method assumes a homogeneous, isotropic, horizontal crust, which is an oversimplification of real earth crustal structure.

3.3. Gaussian-Weighted Common Conversion Point Stacking

[15] In addition to the single station measurements obtained from Hκ stacking, we constructed subsurface images using a modified version of common conversion point (CCP) stacking [e.g., Dueker and Sheehan, 1997; Eagar et al., 2010]. In this method, we back project the receiver function amplitudes along rays toward each corresponding origin. We use the same 1-D velocity model (Table 2) from Eagar et al. [2010], which combines the TNA S wave velocities [Grand and Helmberger, 1984] modified for crustal velocities from Catchings and Mooney [1988b]. We divide our volume into imaging points spaced laterally every 10 km and vertically every 1 km to a depth of 80 km. To compute piercing points of converted (Pds) waves at each depth, we used the spherical traveltime equation

  • equation image

where R(ri) is the Earth's radius from each ith depth shell r in km, Δr is the depth interval, and p is the ray parameter expressed in sec/radian. From this point, our method deviates from CCP stacking in that we do not produce linear stacks based on location binning of piercing points. Because the imaging targets are shallow (<50 km) and the USArray TA station spacing is large (∼70 km), very large CCP bins would be necessary for analysis. These bins would be sparsely populated, resulting in stacks that would be heavily influenced in many cases by only one station. The results would require interpolation and smoothing poststack. To circumvent this complication, we compute the amplitude, Ac, at image point xc, from the weighted stack of each jth receiver function amplitude, Aj, by

  • equation image

where weights are determined by the horizontal distance of the receiver function piercing point xj from the image point by a 2-D Gaussian function,

  • equation image

with standard deviation G. This method borrows the concept of Gaussian weighting from the pseudostation stacking method [Neal and Pavlis, 1999], which uses a Gaussian smoother to interpolate data from an irregularly spaced array to a synthetic array with regular spacing. Our method differs from pseudostation stacking, however, in that the Gaussian smoother is applied to the receiver functions after ray tracing instead of directly to the seismograms. We refer to our method as Gaussian-weighted common conversion point stacking (GCCP).

Table 2. One-Dimensional Velocity Model for Time to Depth Conversions in GCCP Stacking
Depth (km)Vpa (km/s)Vsb (km/s)
06.253.47
257.204.00
388.104.40
508.004.35
757.954.32
1007.894.29

[16] Ideally, G should be chosen to reflect approximately the Fresnel zone of the receiver functions. For our 0.5 Hz receiver functions, the Fresnel zone is ∼13 km at a Moho depth of 38 km (the Moho depth in our 1-D velocity model). While a value of G = 13 km works for regions of the HLP array where station spacing is small, much of our imaging area is covered by broader ∼70 km station spacing of the USArray TA. We therefore chose a value of G = 35 km to allow some significant portion of data to be included from at least one standard deviation in distance away from each imaging point across our entire study region.

4. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

4.1. Receiver Function Observations

[17] Receiver functions at stations within our data set display different characteristics in quality and complexity. Nearly 70% of the stations show a strong, coherent Ps arrival, whereas Ps appears, to a varying degree, ambiguous, variable, or nonexistent at the remaining stations. Important issues that obscure the Ps observation include (1) strong converters between the direct P and Ps, which are probably due to intracrustal layers; (2) apparent late arriving direct P phases, which likely originate from high-amplitude reverberations off low-velocity sedimentary layers; or (3) low Ps amplitudes, presumably due to a diffuse or complex Moho boundary. The PpPs reverberation is observed at the majority of stations, but is not as consistently visible as Ps. PsPs is rarely observed as a clear arrival and is only visible in a few receiver functions in our data set.

[18] We rank the overall solution at each station based both on the signal-to-noise ratio of the Ps, PpPs, and PsPs phases and an estimate of complexity. We categorize stations as: high quality, meaning that all three arrivals are observed; medium quality, meaning only one or two arrivals are observed; or low-quality data, meaning very high signal-to-noise ratio and/or not enough data (less than 10 records). Low-quality stations are excluded from further analysis. The high- and medium-quality stations are then evaluated based on complexity. Stations are classified as “complex” if they have a highly variable or diffuse Ps, significant coherent transverse energy, back azimuthal variations in phase amplitude and arrival times, late arriving direct P, or strong intracrustal arrivals. For now we recognize that these features may indicate structure beneath the station that deviates from a flat-lying, isotropic, homogeneous crust assumed by the H − κ method. Future detailed analysis is necessary to determine the exact structural causes for the complexities. A station classified as “simple” exhibits arrivals that follow normal moveout and have no complex characteristics. We then divide our ranked results in the following manner: I, high quality, simple; II, medium quality, simple; III, high quality, complex; IV, medium quality, complex; and V, low quality. The rankings assigned to each station are shown in Figure 5 (see Data Set S1 for the complete list).

image

Figure 5. Individual station and receiver function rankings for quality and complexity. See section 4.1 for ranking criteria.

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[19] To illustrate some of the features within our receiver functions, we describe stations XC-ID008, XC-OR041, XC-OR120, and XC-OR051 shown in Figures 6 and 7. XC-ID008 is a rank I station that shows all three phases and has a well constrained H − κ solution (Figure 6a). This station is located on the Owyhee Plateau, where many of the stations show similar data quality, indicating that the crust is relatively flat and laterally homogeneous. XC-OR041 is located just to the west of Newberry volcano and has very complex receiver functions, with a rank IV classification (Figure 6b). The largest pulse arrives at 1 s, followed by high-amplitude arrivals. A very low velocity sediment layer near the surface likely accounts for a strong converter soon after the direct P that also produces reverberations that overprint later crustal reverberations. Many stations on the eastern flank of the Cascades show this same pattern. More scrutiny and subjectivity was given to trace editing in these instances, where records not showing a clear Ps arrival were discarded. In this case, the H − κ stacking does not work as well, producing a less constrained solution with more uncertainty than we can quantify given the ambiguity of Moho phase arrivals. XC-OR120 is a rank III station (high-quality, complex structure) in the southeastern part of the HLP with an intracrustal converter (Figure 6c). This arrival stands out as nearly the same amplitude as the Ps. The H − κ stack is still good and well constrained. It should be noted hat the intracrustal layer does produce its own set of reverberations. An arrival that appears at ∼9 s could be the first reverberation in the intracrustal layer and a negative arrival at ∼11 s could be the second reverberation. We note that given a certain thickness and velocity ratio of the upper crust could allow the second intracrustal reverberation to destructively interfere with the PpPs arrival. The result would bias the H − κ stacking as demonstrated in Champion et al. [2006]. This is not a problem for every intracrustal layer, including XC-OR120, but could have consequences when interpreting other stations. XC-OR051 is another rank III station that exhibits an intracrustal converter, a strong negative arrival prior to Ps, possibly from a low-velocity layer just above the Moho, as well as several variations with respect to back azimuth (Figure 7a). The arrival of the intracrustal converter is earlier from southwestern back azimuths than from northern and eastern back azimuths. This change is also demonstrated in a polarity reversal seen on the transverse receiver functions around this same time (Figure 7b). This characteristic is likely attributed to anisotropy or a dipping layer within the crust [Cassidy, 1992]. The Ps is observed as a single peak from all back azimuths except from the W and NW, where a double peaked Ps is detected. There is a high-energy positive arrival on the transverse component related to the double peak indicating a complex Moho structure that is creating out-of-plane energy. This observation is not easily explainable without further modeling, but it remains that this station demonstrates highly complex crustal structure that is likely to alter the solution from Hκ stacking (Figure 7c).

image

Figure 6. Receiver functions and H − κ stacks from three stations in the High Lava Plains array. (top) Normalized receiver functions in black and linear stack in gray. (middle) Receiver functions as a function of ray parameter. (bottom) H − κ stacking grid. White circles denote one standard deviation contour from maximum normalized amplitude. (a) Station XC-ID008 shows very clear Ps and reverberations with no complexities. The H − κ stacking result is well constrained. (b) Station XC-OR041 shows a nonzero direct P, and Moho reverberations are not obvious. The H − κ stacking result has large tradeoffs and is not well constrained. (c) Station XC-OR120 shows a clear intracrustal conversion with otherwise simple Ps and reverberations. The H − κ stacking result is also well constrained.

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image

Figure 7. (a) Radial and (b) transverse receiver functions and (c) H − κ stack from station XC-OR051. Amplitude plots are the same as the plots in Figure 6 (top). Back azimuth plots in Figures 7a and 7b show receiver functions versus back azimuth. In Figure 7a, radial receiver functions show back azimuthal variations in an intracrustal positive; a strong, persistent intracrustal negative; and a double Ps for events from the NW. In Figure 7b, transverse receiver functions show similar energy from the intracrustal positive, as well as sub-Moho energy for events from the NW. In Figure 7c, the H − κ stacking grid shows a broad zone of energy associated with the Ps conversion.

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4.2. Crustal Thickness

[20] The Hκ stacking solutions reveal significant variations in crustal thickness across the region. Figure 8 shows Moho depths derived from the H − κ method from each station smoothed over a 10 × 10 km grid using splines under tension with a tension factor of 0.3 using the Generic Mapping Tools [Smith and Wessel, 1990]. The results from GCCP stacking for three cross sections are displayed in Figure 9, with H − κ Moho depths overlain for comparison. Both H − κ and GCCP stacking show general agreement in the pattern of Moho topography (Figure 9). Discrepancies between the two results are mostly linear shifts and both exhibit the same broad-scale patterns (Figure S1). For instance, in the western HLP, the Moho derived from GCCP stacking is ∼5 km deeper than the Moho derived from H − κ stacking. Lower crustal velocities than are contained within our 1-D velocity model for GCCP stacking, as revealed by tomographic models from ambient seismic noise [e.g., Bensen et al., 2009; Moschetti et al., 2010], might explain this effect. However, we chose not to use these tomographic models for our analysis primarily because of their coarser lateral resolution and parameterization difficulties. Other areas show individual differences that probably originate from a combination of uncertainties in the velocity model, complexities in crustal structure, and quality of the receiver functions since many occur at rank IV stations (Figure 5). Unless otherwise noted, we report results from H − κ stacking in this section.

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Figure 8. Map of Moho depth derived from Hκ stacking analysis. Single station results (colored circles) are smoothed over a 10 × 10 km grid using splines under tension with a tension factor of 0.3 using the Generic Mapping Tools [Smith and Wessel, 1990]. Red colors denote shallower Moho, blue colors denote deeper Moho, and gray regions represent areas of limited sampling in this study. Black solid lines denote 5 km contours. The 87Sr/86Sr isopleths of 0.704 and 0.706 (“0.704” and “0.706” lines) are denoted by black dashed lines. Geologic provinces include Cascade volcanic arc (CM), Blue Mountains (BM), High Lava Plains (HLP), Columbia River basin (CRB), Snake River Plain (SRP), Idaho batholith (IB), Owyhee Plateau (OP), Modoc Plateau (MP), and Great Basin (GB).

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image

Figure 9. Cross sections of Moho depths and crustal features. Geologic and geochemical provinces are labeled as in Figure 8. (a) Map of seismic stations and locations of cross-sectional profiles. (b–d) Colored background shows amplitudes from GCCP stacking using the 1-D velocity model in Table 2. Solid line with depth labels denotes Moho value picked from maximum amplitudes in GCCP stacks. Dotted black lines labeled LVZ are areas of strong negative amplitudes in the crust. White stars represent Hκ Moho depths (errors range from ±2 to ±5 km) from the nearest stations along each profile that use regional refraction line crustal velocities in Table 1. Figure 9b shows profile A–A′, E-W cross section. Figure 9c shows profile B–B′, NW-SE cross section. Figure 9d shows profile C–C′, N-S cross section.

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[21] Our results reveal an average crustal thickness of 42.3 ± 1.2 km beneath the Cascade volcanic arc with eastward extensions of the thick crust both north and south of the HLP in the western Columbia Basin and the Modoc Plateau. Thick crust also occurs in the northern portion of the Idaho Batholith and the Owyhee Plateau. Thinner crust is found beneath the northern Great Basin, HLP, western Snake River Plain/southern Idaho Batholith, the Blue Mountains and the eastern Columbia Basin. Crustal thicknesses within these regions of generally thin crust range from ∼25 km (central HLP) to ∼35 km (western Snake River Plain/southern Idaho Batholith).

[22] Some of the lateral transitions in Moho depth are abrupt (∼20 km or less) and correlate well with geologic terrane boundaries. Perhaps the most distinct boundary evident in our images is the transition from the HLP to the Owyhee Plateau. The high concentration of HLP stations in this region helps to determine precisely the western edge of the Owyhee Plateau at depth, with a rapid 7 km increase in crustal thickness from ∼31 km to ∼38 km over less than 20 km laterally (∼31 km to ∼38 km using Hκ (Figure 8); ∼35 km to ∼42 km using GCCP (Figure 9c)). The eastern boundary of this thickened terrane is not distinguishable given the eastern edge of our study region. Another sharp change in the Moho is evident across the middle of the southern lobe of the Idaho Batholith, near the inferred southern boundary of the Belt Basin [e.g., Harrison, 1972], where the Moho abruptly dips from ∼30 km to ∼40 km (Figure 9b).

[23] One anomalous case of a sharp transition is the apparent abrupt thinning from the Cascades to the HLP (Figure 8). In this region, the Hκ method may be biased from conversions off the subducting oceanic Moho, as well as other reverberations. The results from GCCP receiver function stacking, on the other hand, are not affected by reverberations from the slab in the same way as are those from the Hκ method; therefore, the GCCP images provide a more reliable estimate of the proper Moho depth range in regions of crustal complexity. Comparison between results from the two methods confirms that the Moho depth derived from the Hκ method for several stations in the Cascades is much greater than the values obtained from GCCP stacking (∼41 km (Figure 9b)), and is likely not imaging the Moho, but rather the upper subducting slab interface. The GCCP result is also consistent with scattered wavefield imaging of the subducting slab from Bostock et al. [2002], which shows the continental Moho near 36 km.

[24] Finally, we note that the seismic visibility of the Moho varies across the region and shows patterns that could indicate complex geologic structure that introduce potential imaging problems. An examination of the amplitudes of the receiver functions at the Moho boundary, as mapped from GCCP stacking (Figure 10), show that the most noticeable area of smallest normalized amplitude (<0.15) is observed in an arcuate pattern from the western Snake River Plain/southern Idaho Batholith through southeastern Oregon and into northern Nevada. This pattern coincides with some of the sharpest gradients in the Moho topography (i.e., from the HLP to the Owyhee Plateau) where dipping structures or deformation features along the edge of the Owyhee Plateau may lead to significant scattering of converted waves. To a lesser extent, the Blue and Wallowa Mountains regions also show reduced amplitudes. This area, which is on the edge of the western Idaho Shear Zone and near a significant source region for the Columbia flood basalt flows, may have significant complexities in the crust that also obscure our images. Although characterization of these complexities is beyond the scope of this paper, this observation may point to interesting focus areas for future seismic imaging and analysis.

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Figure 10. Map of Ps amplitudes at Moho depths determined from GCCP stacks. Contouring parameters are the same as in Figure 8. Amplitude contours denoted by white solid lines. Dark gray region outside dashed white line represents area of limited sampling in this study.

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4.3. Poisson's Ratio

[25] Poisson's ratios across the region vary strongly (Figure 11) and regional patterns do not directly correlate with variations in Moho depth. Several areas of extremely low Poisson's ratios, reaching values <0.225, are observed in the northernmost Great Basin. We find consistently low Poisson's ratios across the Idaho Batholith (0.240 ± 0.016), the Modoc Plateau (0.250 ± 0.012), and the northern Great Basin south of the Owyhee Plateau (0.268 ± 0.013). In addition, there is a prominent band of low Poisson's ratios (0.252 ± 0.017) that traverses N-S across the Blue Mountains, the Harney Basin, down Steen's Mountain, and into the northern Great Basin. The high station density within this zone provides added confidence that the sharpness of this feature is well resolved. Conversely, the western HLP is characterized by high Poisson's ratios, well over 0.300 in most places and averaging 0.304 ± 0.013 (Figure 11). Interestingly, the highest values are located just east of the Cascade arc, and are bisected by slightly lower values along the age progressive track of the HLP.

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Figure 11. Map of Poisson's ratios derived from Hκ stacking analysis. Smoothing parameters and geological/geochemical features are the same as in Figure 8. Black solid lines denote 0.025 contours.

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5. Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[26] Overall, we find clear patterns of crustal features that provide new constraints on the patterns of volcanism in the High Lava Plains and surrounding region. Here we focus on the relationships between crustal characteristics and specific geologic provinces across the region. In most areas, the interpretation of observed crustal structure with tectonic history, expected bulk crustal composition, and/or geochemical constraints is straightforward. Interpretation for a few areas, however, is less obvious given crustal complexities that will likely require further study.

[27] The Owyhee Plateau is a unique crustal block surrounded by multiple extensive magmatic zones, including the central Snake River Plain, the eastern HLP, and the northern Great Basin. It shows many similar characteristics of other continental plateaus, such as the Colorado Plateau, which possess thick crust and relatively undeformed interiors. From both Hκ and GCCP stacking, the Moho appears to be a sharp, flat-lying interface ∼40 km deep (Figures 8 and 9b). Evidence of crustal simplicity include a large number of rank I stations (Figure 5) and the absence of significant intracrustal complexity on both radial and transverse receiver functions. Our results are consistent with the view that the Owyhee Plateau has largely resisted significant deformation and has acted as an isolated thick crustal block during Cenozoic tectonism [Shoemaker, 2004] despite being surrounded by extensional zones (Figure 1) of the Oregon-Idaho Graben and western Snake River Plain [Cummings et al., 2000], the southeastern HLP to the west [e.g., Pezzopane and Weldon, 1993; McCaffrey et al., 2007], and the northern Great Basin to the south [e.g., Zoback et al., 1994; Lerch et al., 2007]. The average Poisson's ratio of the Owyhee Plateau (0.270 ± 0.013) is similar to the global average for Precambrian platforms [Zandt and Ammon, 1995], also consistent with the concept that a package of thick Precambrian crust underlies Cenozoic volcanism expressed at the surface.

[28] Along the well-defined Owyhee Plateau crustal margins, the observed crustal complexity appears to reflect cratonic modification due to the extensive tectonomagmatism experienced by the region over the past 20+ My. For instance, low Ps amplitudes delineate the northern, western, and southern margins of the Owyhee Plateau (Figure 10) and probably represent areas of strong crustal heterogeneity/complexity. We suggest that this complexity originates from either crustal anisotropy or a dipping Moho interface, both of which will attenuate Ps amplitudes when stacking over broad back azimuthal and epicentral distance ranges [e.g., Cassidy, 1992]. Detailed receiver function modeling in future work is necessary to distinguish between these forms of crustal complexity. Further, the zone of higher Poisson's ratios that characterize the western Snake River Plain (0.298 ± 0.011) to the north of the Owyhee Plateau is consistent with significant basaltic volcanism, mafic intrusions, and higher temperatures [Blackwell and Richards, 2004; DeNosaquo et al., 2009]. The sharp jump in crustal thickness from the southeastern HLP is generally consistent with preliminary models from wide-angle seismic refraction data across the HLP that show a similar step in roughly the same region (C. Cox and G. R. Keller, manuscript in preparation, 2011). To the west, the well-defined, sharp edge of the Owyhee Plateau also coincides well with the “0.704” line, while the southern boundary correlates with the “0.706” line (Figures 8 and 9b). These observations are consistent with a model in which this area represents the rapid transition from accreted and tectonically modified oceanic crust to stable cratonic crust. If the crustal boundary extends to lithospheric depths, it may represent the proposed boundary of transitional lithosphere, from oceanic to cratonic, delineated by the “0.704” line to the west and the “0.706” line to the east [Leeman et al., 1992].

[29] The low Poisson's ratios observed for the Idaho Batholith are consistent with a thick crustal section of largely granitic composition [Christensen, 1996]. The distribution of low Poisson's ratios match better the distribution of Cretaceous granites in the Idaho Batholith than does our determined crustal thickness values, where the northern portion of the batholith is underlain by ∼41 km thick crust and the southern portion exhibits significantly thinner (∼34 km) crust (Figure 8). The boundary between thick and thin crust roughly follows the southern boundary of the exposure of the Proterozoic Belt Basin [Harrison, 1972]. The region of thinning also correlates with the region of lowest Ps amplitudes (Figure 10), which may indicate a diffuse Moho boundary beneath the southern Idaho Batholith (Figure 9b). Although the cause of the crustal thinning and diffuse Moho in the Idaho Batholith is still unclear, both features might be expected from intense crustal-scale deformation in the western Idaho shear zone [Leeman et al., 1992] and if the Belt Basin is a back-arc basin developed landward of a circa 1450 Ma convergent margin along western North America [e.g., Ross and Villeneuve, 2003].

[30] The complex magmatic development of the greater High Lava Plains region is also clearly reflected in its crustal structure. First, while the entire HLP region is characterized generally by thin (∼31 km) crust, the zone of thinnest (<30 km) crust does not follow the NW trending time progressive rhyolite track, but rather extends from southern Oregon west of the Steens Mountain escarpment to the Blue Mountains, roughly perpendicular to the direction of extension across the HLP (Figure 8). The pattern of crustal thickness variations thus suggests that the central area of the HLP has been most thinned by Miocene and later extension occurring in eastern Oregon. If the initial crustal thickness was similar to that in the Blue Mountains (∼32 km), a current average thickness of 26 km in the central HLP would require approximately 16% extension, similar to that estimated from paleomagnetic data [Wells and Heller, 1988]. Further, with the exception of a zone near the Steens Mountain escarpment, the eastern boundary of the zone of thinnest crust generally matches well with the “0.704” line, consistent with the idea that the crust beneath eastern Oregon thinned as westward extension translated the Cascades away from the Precambrian boundary of North America [Carlson and Hart, 1987].

[31] The zone of thinnest crust in eastern Oregon is also coincident with significant variations in Poisson's ratios over short spatial scales (Figure 11). Ratios >0.290 that typify much of the HLP volcanic track are generally consistent with a mafic crust [Christensen, 1996], as expected in this area given the extensive middle to late Miocene basaltic volcanism [e.g., Jordan et al., 2004]. The high average Poisson's ratios of 0.295 ± 0.014 throughout the HLP also agree with typical values for mafic rocks thought to compose the accreted oceanic terranes of this region [Christensen, 1996].

[32] The zone between the Cascades and eastern HLP shows extremely high Poisson's ratios (up to ∼0.320) that flank the HLP age progressive track exhibiting slightly lower Poisson's ratios (Figure 11). These well-resolved and robust large ratios are very difficult to explain by rock composition alone, since Poisson's ratios for most rock types fall between 0.250 and 0.300 [Christensen, 1996]. While temperature alone (absent partial melting) may increase Poisson's ratios by a few percent, this effect is insignificant with respect to the influence of composition [Tarkov and Vavakin, 1982; Bratt and Solomon, 1984]. Plausible scenarios that can explain the high Poisson's ratios in our study include (1) the presence of large amounts of serpentinite in the lower crust, which has high Poisson's ratio and very low Vs (0.352 and 2.63 km/s, respectively, at 600 MPa averaged over all temperatures from 0 to 700°C) [Christensen, 1996], or (2) the presence of partial melt in a mafic crust, which would significantly decrease Vs with respect to Vp [e.g., Bratt and Solomon, 1984; Mueller and Massonne, 2001]. While serpentinization of the mantle fore arc has been imaged in Cascadia to the north of our study region [Bostock et al., 2002], it is unlikely that large volumes of serpentinite in the crust extend beneath such a broad region of central Oregon. Further, we do not find evidence for a diffuse crust-mantle boundary, which would be expected to accompany the highly reduced Vs of a serpentinite-rich lower crust (Figure 10).

[33] Given the volcanic history of eastern Oregon, we propose that the broad region of high Poisson's ratios is best explained by the presence of a small degree of partial melt in the middle to lower crust. These areas exist where post-Miocene volcanism has been relatively subdued, at least compared to the axis of the main HLP track [e.g., Smith and Luedke, 1984]. One possible reason for very high Poisson's ratios in these areas is because the small melt fraction in the crust has not been drained, unlike areas directly along the HLP track where crustal melt transport to the surface has occurred, perhaps due to faulting associated with the Brothers Fault Zone. We also observe a spatial correlation between areas of the highest Poisson's ratio and the strongest intracrustal negative receiver function amplitudes (Figure 9). These observations collectively imply strongly reduced crustal S wave velocities, consistent with other regional shear wave velocity models derived from surface waves which document strongly reduced crustal and uppermost mantle velocities in the same region [e.g., Moschetti et al., 2010; Wagner et al., 2010]. Additional supporting evidence consistent with the partial melt hypothesis comes from both high heat flow values across the region [Blackwell and Richards, 2004] and high crustal temperatures suggested by a very shallow Curie temperature isotherm [Bouligand et al., 2009]. Finally, recent models of magnetotelluric data also point to a zone of high conductivity within the lower crust in the same region, which is consistent with the strong presence of fluids including partial melt [Stanley et al., 1990; Patro and Egbert, 2008].

[34] We apply the findings of Hammond and Humphreys [2000] to determine a range of partial melt fraction consistent with these observations. Using a derivative of −7.9% per 1% melt fraction for the estimated ∼3% Vs reduction beneath southern Oregon [Wagner et al., 2010], we calculate a partial melt fraction of ∼0.4%. This value is probably a minimum estimate, since the derivative may be smaller for melt fractions <1% [Hammond and Humphreys, 2000], and because the surface wave inversion used to determine Vs variations is a damped model. To determine an upper bound, we use our average Vp/Vs of 1.95 for this area to determine a value of ∼2% partial melt [Hammond and Humphreys, 2000, Figure 6].

[35] Finally, we note that the region near the Steens Mountain escarpment is particularly intriguing. Dikes exposed in the Steens fault face show this area to be one of the major sources that fed Steens volcanism that erupted 50,000–65,000 km3 of flood basalts beginning at 16.6 Ma [Carlson and Hart, 1987; Brueseke et al., 2007]. The area surrounding the Steens escarpment is clearly reflected in the regional crustal structure, as both a zone of slightly thickened crust forming the boundary between the thinnest HLP crust and the “0.704 line” (Figure 8), and a zone of anomalously low Poisson's ratio (Figure 11). Carlson and Hart [1987] estimated that the generally evolved composition of most Steens basalt resulted from fractionation of ∼40% by mass of a primitive basaltic magma. Taking the area of the low Poisson's ratio at Steens Mountain (approximately 130 × 50 km), the 40% fractionation of 50,000 km3 of basalt would create a midcrustal cumulate pile ∼3 km thick, similar in value to the additional crust observed beneath the Steens Mountain area. Petrologic modeling suggests that the cumulate pile would consist of roughly 60% plagioclase and 20% each of olivine and pyroxene [Carlson and Hart, 1987] and perhaps is responsible for the low Poisson's ratio in this area. We note that the source dike areas of the Columbia River flood basalts (Figure 1), both of the Picture Gorge unit erupted from the Monument dike swarm in the Blue Mountains and the Chief Joseph dike swarms along the Washington-Idaho-Oregon borders, also show thickened crust and low Poisson's ratios. These crustal characteristics thus appear to be caused by the remains of midcrustal magma chambers that served as accumulation and fractionation reservoirs for the flood basalt flows.

6. Conclusions

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[36] Receiver function analysis beneath the High Lava Plains and surrounding regions in the Pacific Northwest, United States reveal a complex topography on the Moho and varying crustal structures and velocities. We observe areas of thin crust beneath the Blue Mountain terrane, HLP, and northern Great Basin, whereas we find thick crust beneath the flanking regions of the Cascade volcanic arc, Idaho Batholith and Snake River Plain, and the Owyhee Plateau. Poisson's ratio is generally low in the Idaho Batholith, consistent with widespread exposure of granitic plutons in the region. The Owyhee Plateau is an isolated crustal block similar to other continental plateaus in that it is thick and appears to have resisted deformation relative to surrounding regions. Its boundaries are well defined to at least Moho depths and are consistent with geochemical boundaries that delineate younger accreted terranes to the west from older cratonic regions to the east. The average Poisson's ratio for the Owyhee Plateau is also consistent with that of stable Precambrian crust globally. In contrast, the HLP has an irregular Moho topography that shows a gentle SE dip and is in general the shallowest in the region. The thinned crust of the HLP is consistent with ∼16% extension across eastern Oregon. Evidence for mafic underplating and intraplating in the central HLP is seen along the age progressive rhyolitic track, but is most prominent in the areas of the dike swarms that fed both the Steens and Columbia River flood basalts. For instance, the area of the N-S band of low Poisson's ratios near Steens is consistent with a thickening of the crust that is roughly equivalent to the speculated cumulate pile in the midcrust that served as the source of the massive flood basalts. Finally, the crust likely contains a small degree of partial melt east of the Cascades and both north and south of the HLP magmatic track. The presence of melt is indicated by extremely high Poisson's ratios, low crustal S wave velocities, high crustal temperatures, and high lower crustal conductivity. The HLP track itself may mark the existence of a magma drainage zone where crustal melts were more efficiently transported to the surface.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

[37] This work would not have been possible without the high-quality seismic data provided through the hard work of the Earthscope/USArray Transportable Array and the High Lava Plains (HLP) Seismic Experiment teams (http://www.dtm.ciw.edu/research/HLP) and the services of the Incorporated Research Institutions for Seismology (IRIS) Data Management Center (DMC). As always, the IRIS Program for Array Seismic Studies of the Continental Lithosphere (PASSCAL) provided world-class technical field support. Data from the TA network were made freely available as part of the EarthScope/USArray facility supported by the National Science Foundation, Major Research Facility program, under Cooperative Agreement EAR-0350030. The facilities of the IRIS Data Management System, and specifically the IRIS DMC, were used for access to waveform data and metadata required in this study. The IRIS DMC is funded through the National Science Foundation and specifically the GEO Directorate through the Instrumentation and Facilities Program of the National Science Foundation under Cooperative Agreement EAR-0004370. A portion of the data was also provided from long-lived regional and national networks, including the Advanced National Seismic System, the University of Oregon Regional Network, the Berkeley Digital Seismograph Network, and the Cascade Chain Volcano Monitoring Network. We particularly acknowledge the contributions from the dozens of people involved in the HLP project (http://www.dtm.ciw.edu/research/HLP). A special thanks goes to Jenda Johnson, whose contributions to the project have been innumerable and immeasurable, and Steven Golden for providing field and data support. We also thank the Eastern Oregon Agricultural Research Center (EOARC) stations in Burns, Oregon, and Riley, Oregon, for providing a dual base of operations for the HLP seismic field effort. In particular, Tony Svejcar, Joel Swindlehurst, Verne Brown Jr., and Lynn Carlon were always available to enable use of EOARC facilities. Thanks to Catherine Cox and Randy Keller for providing preliminary velocity models from the active source experiment that is coincident with the dense profiles in the broadband deployment of the HLP project. We would also like to acknowledge the work and productive discussions on the crustal evolution with the other PIs of the HLP project, including Anita Grunder, Bill Hart, Tim Grove, Randy Keller, Steve Harder, and Bob Duncan. This research was supported by National Science Foundation awards EAR-0548288 (MJF EarthScope CAREER grant), EAR-0507248 (MJF Continental Dynamics High Lava Plains grant), and EAR-0506914 (DEJ/RWC Continental Dynamics High Lava Plains grant).

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. High Lava Plains Passive Seismic Experiment and Data Collection
  5. 3. Methods
  6. 4. Results
  7. 5. Discussion
  8. 6. Conclusions
  9. Acknowledgments
  10. References
  11. Supporting Information

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jgrb16667-sup-0003-ds01.xlsapplication/excel84KData Set S1. Complete results from H − κ stacking analysis.
jgrb16667-sup-0004-fs01.epsPS document6940KFigure S1. Map of Moho depth derived from GCCP stacking analysis.
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